Volunteer Moderation as Situated Civic Labor in Local Information InfrastructuresLocal information is essential for civic engagement, community belonging and well-being, and collective action. As more U.S. communities become "news deserts" without local newspapers or broadcast media, neighborhood- and municipality-level groups on platforms like Facebook, Nextdoor, and Reddit have become key nodes in local information infrastructure. This paper examines how volunteer moderators of these local online groups contribute to sustaining local information infrastructure, focusing on how they understand their groups’ informational function, the roles they assume to realize this function, and the skills they mobilize to fulfill perceived roles. Drawing on an Asynchronous Remote Community study and in-depth interviews with U.S.-based moderators, we conceptualize local volunteer moderation as situated civic labor, emphasizing the interpretive, relational, and context-contingent nature of their work. We offer design implications for platforms to support local knowledge and discretion and sustain democratic practices to strengthen the civic potential of online spaces to serve their local communities.2026KCKelley Cotter et al.Pennsylvania State UniversityContent Moderation & Platform GovernanceCommunity Engagement & Civic TechnologyCHI
Reclaiming VR Design Authority: Deaf Signers Shaping Immersive ClassroomsDeaf students face a persistent visual attention split between signer and instructional materials. Although virtual reality (VR) is often promoted as an educational solution, it typically reinforces hearing norms (e.g., caption overlays or interpreter boxes onto hearing classrooms). Our work foregrounds Deaf leadership and reclaims VR design authority: in a mixed-hearing team led by Deaf scholars, we designed and evaluated a VR classroom prototype featuring three signer-placement modes: corner, parallel, and transparent. Twelve Deaf participants explored the prototype during a 15-minute lecture and participated in qualitative semi-structured interviews. Participants reported reduced attention split and improved visibility, and suggested VR may support flexibility and comprehension in Deaf learning. From these reflections, we introduce a five-dimension conceptual framework---proximity, customizability, visual efficiency, cultural fit, and task flexibility---that organizes how Deaf signers evaluate signer placements. This work moves Deaf Tech theory into practice, opening pathways for future Deaf-centered, culturally grounded HCI.2026SHShuxu Huffman et al.Gallaudet UniversitySocial & Collaborative VRVR Medical Training & RehabilitationDeaf & Hard-of-Hearing Support (Captions, Sign Language, Vibration)CHI
Repurposing Audio Playback Tools to Test Human Localization with 6DoF SoundSix-degree-of-freedom audio is a growing interest in interactive software, but it does not easily conform to object-based rendering when achieved with arrays of ambisonics microphones. Prior studies rely on subjective metrics also, which do not clearly indicate how this additional audio interaction might aid a human in a localization task—an indication of enhanced spatial awareness of a sound event. In this paper, we propose an alternative recording and playback technique to achieve six-degree-of-freedom audio to minimize recording overhead, yield object-based rendering, and verify enhanced spatialization through objective testing. The approach taken in this paper utilizes existing audio playback tools in the Unity game engine, and can be redeployed quickly to allow researchers outside of audio engineering exploration in six-degree-of-freedom audio applications. Two studies were conducted within a group of participants using a Microsoft Hololens 2—testing for interpretation of directional sound cues in a stationary position, and testing the proposed technique in a mobile task. Participants were able to discern additional information within the front-facing "blind spots" and were effectively perfect in a localization task with the proposed audio technique. Participants did not achieve the same performance level with a head-related transfer function alone—indicating meaningful cueing with six-degree-of-freedom sound.2025DRDan Rehberg et al.Foot & Wrist InteractionEye Tracking & Gaze InteractionMusic Composition & Sound Design ToolsUIST
An Artists' Perspectives on Natural Interactions for Virtual Reality 3D SketchingVirtual Reality (VR) applications like OpenBrush offer artists access to 3D sketching tools within the digital 3D virtual space. These 3D sketching tools allow users to ``paint'' using virtual digital strokes that emulate real-world mark-making. Yet, users paint these strokes through (unimodal) VR controllers. Given that sketching in VR is a relatively nascent field, this paper investigates ways to expand our understanding of sketching in virtual space, taking full advantage of what an immersive digital canvas offers. Through a study conducted with the participation of artists, we identify potential methods for natural multimodal and unimodal interaction techniques in 3D sketching. These methods demonstrate ways to incrementally improve existing interaction techniques and incorporate artistic feedback into the design.2024RRRichard Rodriguez et al.Colorado State University3D Modeling & AnimationDigital Art Installations & Interactive PerformanceCHI
Trust-Aware Planning: Modeling Trust Evolution in Iterated Human-Robot InteractionTrust between team members is an essential requirement for any successful cooperation. Thus, engendering and maintaining the fellow team members' trust becomes a central responsibility for any member trying to not only successfully participate in the task but to ensure the team achieves its goals. The problem of trust management is particularly challenging in mixed human-robot teams where the human and the robot may have different models about the task at hand and thus may have different expectations regarding the current course of action, thereby forcing the robot to focus on the costly explicable behavior. We propose a computational model for capturing and modulating trust in such iterated human-robot interaction settings, where the human adopts a supervisory role. In our model, the robot integrates human's trust and their expectations about the robot into its planning process to build and maintain trust over the interaction horizon. By establishing the required level of trust, the robot can focus on maximizing the team goal by eschewing explicit explanatory or explicable behavior without worrying about the human supervisor monitoring and intervening to stop behaviors they may not necessarily understand. We model this reasoning about trust levels as a meta reasoning process over individual planning tasks. We additionally validate our model through a human subject experiment.2023ZZZahra Zahedi et al.AI-Assisted Decision-Making & AutomationHuman-Robot Collaboration (HRC)HRI
In UX We Trust: Investigation of Aesthetics and Usability of Driver-Vehicle Interfaces and Their Impact on the Perception of Automated DrivingIn the evolution of technical systems, freedom from error and early adoption plays a major role for market success and to maintain competitiveness. In the case of automated driving, we see that faulty systems are put into operation and users trust these systems, often without any restrictions. Trust and use are often associated with users' experience of the driver-vehicle interfaces and interior design. In this work, we present the results of our investigations on factors that influence the perception of automated driving. In a simulator study, N=48 participants had to drive a SAE level 2 vehicle with either perfect or faulty driving function. As a secondary activity, participants had to solve tasks on an infotainment system with varying aesthetics and usability (2x2). Results reveal that the interaction of conditions significantly influences trust and UX of the vehicle system. Our conclusion is that all aspects of vehicle design cumulate to system and trust perception.2019AFAnna-Katharina Frison et al.Technische Hochschule Ingolstadt & Johannes Kepler UniversityAutomated Driving Interface & Takeover DesignIn-Vehicle Haptic, Audio & Multimodal FeedbackAI-Assisted Decision-Making & AutomationCHI
EASEL: Easy Automatic Segmentation Event LabelerVideo annotation is a vital part of research examining gestural and multimodal interaction as well as computer vision, machine learning, and interface design. However, annotation is a difficult, time-consuming task that requires high cognitive effort. Existing tools for labeling and annotation still require users to manually label most of the data, limiting their helpfulness. In this paper, we present the Easy Automatic Segmentation Event Labeler (EASEL), a tool supporting gesture analysis. EASEL streamlines the annotation process by introducing assisted annotation, using automatic gesture segmentation and recognition to automatically annotate gestures. To evaluate the efficacy of assisted annotation, we conducted a user study with 24 participants and found that assisted annotation decreased the time needed to annotate videos with no difference in accuracy compared with manual annotation. The results of our study demonstrate the benefit of adding computational intelligence to video and audio annotation tasks.2018IWIsaac Decheng Wang et al.Electrical Muscle Stimulation (EMS)Human Pose & Activity RecognitionComputational Methods in HCIIUI
Never Too Old, Cold or Dry to Watch the Sky: A Survival Analysis of Citizen Science VolunteerismCoCoRaHS is a multinational citizen science project for observing precipitation. Like many citizen science projects, volunteer retention is a key measure of engagement and data quality. Through survival analysis, we found that participant age (self-reported at account creation) is a significant predictor of retention. Compared to all other age groups, participants aged 60-70 are much more likely to sign up for CoCoRaHS, and to remain active for several years. We also measured the influence of task difficulty and the relative frequency of rain, finding small but statistically significant and counterintuitive effects. Finally, we confirmed previous work showing that participation levels within the first month are highly predictive of eventual retention. We conclude with implications for observational citizen science projects and crowdsourcing research in general.2018SSS. Andrew Sheppard et al.Citizen Science and Scientific ResearchCSCW