注目の論文一覧

Plants are rarely positioned as active participants in digital games, serving as decorative elements or passive sensors. We present Plant.play(), a plant–digital game system that positions a living plant as the sole player in a pet-simulation game. Using bioelectrical signals, environmental data, and circadian rhythms, the plant autonomously performs caregiving actions while humans engage as observers. A workshop with five game experts informed the system's design, which was then implemented and deployed in a four-day exhibition. Observational fieldwork and interviews with twelve visitors revealed how people initially sought control, then gradually shifted toward interpreting the plant's slow, unpredictable, and impartial behaviors as meaningful play. Participants formed emotional connections with both the plant and the virtual pet, extending these reflections to their relationships with nonhuman beings. Our findings contribute empirical insights into interpretive engagement with nonhuman actors and offer design considerations for future plant–digital game systems that embrace materiality, perceived agency, and more-than-human perspectives.

In social virtual reality (VR) platforms, players can embody "non-human" avatars, which are representations whose appearance or skeletal structure diverge from typical human characteristics. This capability fosters the emergence of distinctive cultures of social interaction. This paper reports on interviews with users who employ such avatars, investigating (1) motivations for their adoption, (2) their impact on social interactions, and (3) challenges encountered when employing them in social contexts. Our findings reveal that users adopt "non-human" avatars both to escape the expectations and norms associated with the human body—thereby enabling more relaxed social communication—and to gain access to new forms of embodied experience and creative self-expression. The study also provides empirical evidence and discussion on the cultures of social interaction mediated by alternative embodiments, changes in bodily perception resulting from prolonged use, functional and social challenges related to avatar use, and the design strategies and etiquette practices developed to overcome them.

This paper uses research through game design to explore how we can make video games that invite players to invent their own personal play-practices through making and changing rules. Through a reflective process of designing and playtesting a multiplayer game in which changing rules and parameters is the central mechanic, we have identified how we can create opportunities for players to exert their own creative authority on the structure of their play-practices. As our contribution, we present three design themes which aim to invite player authorship on practices of gameplay: opening up digital rules and parameters, bringing internal rules to the surface, and leaving space for internal goals. We also bring a larger discussion of these design patterns in which we investigate the duality of responsibility and freedom in play when we design for player creativity, and the role of video games as tools to make metagames.

Ring interfaces have gained attention in wearable technology for their lightweight and hands-free design. However, their compact form factor limits them to conveying simple information, such as direction or notification, through vibration, electrotactile, or force feedback. In this paper, we introduce HaRing, a novel haptic ring interface equipped with a 4 × 6 pin array display. This dynamic display delivers rich spatial patterns that simple vibration cannot express, effectively conveying high-dimensional information such as directions, semantic symbols, and letters. Its design enables one-handed, eyes-free interaction that does not interfere with visual tasks. We conducted a series of perceptual and user studies to demonstrate its effectiveness, showing a high recognition accuracy of over 94% for complex letters after a brief training period. We anticipate that HaRing can serve as an innovative haptic-only interface for multitasking in real-world or VR environments with high visual load.

Internet memes are central to online communication, yet their visual humor is often lost in face-to-face (F2F) conversations. Augmented reality (AR) offers new ways to bring memes into F2F interactions, but it is unclear how memes can be integrated into F2F conversations using AR, and how they impact conversational dynamics. We surveyed meme users (N=29) to understand motivations and challenges in visualising memes in F2F conversations. With these insights, we developed an AR meme-sharing prototype and invited 12 pairs of friends to design AR visualizations for their memes and use them in conversations. Our analysis reveals two AR-unique visualizations: merging memes with one's body (The-Meme-On-Me) and situating oneself in meme environment (Me-In-The-Meme). We observed two integration patterns: using speech as setup before a meme punchline, and showing memes simultaneously with speech to amplify humor. We report users’ reactions toward AR memes, showing how it enables playful social interaction.

As Artificial Intelligence (AI) conversational agents become widespread, people are increasingly using them for health information seeking. The use of off-the-shelf conversational agents for health information seeking could place high metacognitive demands (the need for extensive monitoring and control of one's own thought process) on individuals, which could compromise their experience of seeking health information. However, currently, the specific demands that arise while using conversational agents for health information seeking, and the strategies people use to cope with those demands, remain unknown. To address these gaps, we conducted a think-aloud study with 15 participants as they sought health information using our off-the-shelf AI conversational agent. We identified the metacognitive demands such systems impose, the strategies people adopt in response, and propose considerations for designing beyond off-the-shelf interfaces to reduce these demands and support better user experiences and affordances in health information seeking.

This study investigates how avatar customization in virtual reality (VR) impacts trust formation between unacquainted individuals and how such trust transfers to subsequent face-to-face (FtF) meetings. A user study with 48 participants was conducted, where participants were assigned to either a ``Similar-Self'' condition, with avatars resembling their real-world appearance, or an ``Alt-Self'' condition, with creative avatars. The results showed that ``Similar-Self'' avatars led to higher initial integrity-based trust perceptions, though both avatar conditions exhibited similar trust growth during VR encounters. Trust carried over from VR to FtF with a brief recalibration period and ultimately increased beyond VR levels in FtF encounters. This research provides insights into how VR can support the development of trust in early-stage interactions and offers implications for Social VR platforms to better support trustworthy interactions across virtual-physical boundaries.

We propose and explore the concept of Partial Participation, facilitating remote collaborators to contribute to meetings in which they are not able to fully participate via an AI agent acting as a proxy. During the meeting, users can monitor LLM-generated real-time meeting updates and respond to questions posed by other attendees. Through a mixed-methods user study with 24 participants using our prototype, ProxyMe, we investigated how the frequency of updates (high vs. low) and the type of response style (multiple choice vs. text input) impact perceived presence and mental workload. Our findings reveal that no single setup is universally optimal, and the partial participation fosters a moderate level of social presence and attentional mental workload. Our contributions introduce partial participation as a new paradigm for remote collaboration and highlight how AI can mediate participation when full presence is not feasible.

Current touch-based interactions on earphones are limited by hygiene concerns and the small interaction surface. Recent works attempt to bypass these issues with mid-air gesture systems using active acoustic sensing. However, these signals may be audible and pose potential hearing risks. To address this, we propose FingerBar, a mid-air gesture recognition system for earphones that relies solely on microphones without active signal transmission. FingerBar leverages the distinctive friction sounds generated by finger gestures to achieve gesture recognition. We design a gesture filtering pipeline to maintain robustness against daily noise. An adversarial training strategy further enhances user-independent performance. From a set of 16 gestures, we identify the 7 most suitable for FingerBar based on user acceptability. Extensive evaluations demonstrate high accuracy and robustness. Furthermore, a user study confirms the practicality and acceptability of the system. Our findings highlight the promise of passive acoustic sensing as a user-friendly interaction modality for earphones.

Interacting with multiple objects simultaneously makes us fast. A pre-step to this interaction is to select the objects, i.e., multi-object selection, which is enabled through two steps: (1) toggling multi-selection mode --- mode-switching --- and then (2) selecting all the intended objects --- subselection. In extended reality (XR), each step can be performed with the eyes, hands, and voice. To examine how design choices affect user performance, we evaluated four mode-switching (\Semipinch, \Fullpinch, \Doublepinch, and \Voice) and three subselection techniques (Gaze+Dwell, Gaze+Pinch, and Gaze+Voice) in a user study. Results revealed that while \Doublepinch paired with Gaze+Pinch yielded the highest overall performance, \Semipinch achieved the lowest performance. Although \Voice-based mode-switching showed benefits, Gaze+Voice subselection was less favored, as the required repetitive vocal commands were perceived as tedious. Overall, these findings provide empirical insights and inform design recommendations for multi-selection techniques in XR.

The dark patterns, deceptive interface designs manipulating user behaviors, have been extensively studied for their effects on human decision-making and autonomy. Yet, with the rising prominence of LLM-powered GUI agents that automate tasks from high-level intents, understanding how dark patterns affect agents is increasingly important. We present a two-phase empirical study examining how agents, human participants, and human-AI teams respond to 16 types of dark patterns across diverse scenarios. Phase 1 highlights that agents often fail to recognize dark patterns, and even when aware, prioritize task completion over protective action. Phase 2 revealed divergent failure modes: humans succumb due to cognitive shortcuts and habitual compliance, while agents falter from procedural blind spots. Human oversight improved avoidance but introduced costs such as attentional tunneling and cognitive load. Our findings show neither humans nor agents are uniformly resilient, and collaboration introduces new vulnerabilities, suggesting design needs for transparency, adjustable autonomy, and oversight.

Video game archaeology is a relatively new field. This can involve studying players through the traces they leave in digital game worlds, though only limited work of this kind exists. Furthermore, the potential of these methods to record ephemeral play experiences for preservation purposes has not been widely explored. We conducted an archaeological survey of five sites in Elden Ring, taking place directly before, during and after the release of a major expansion. We present what is, to our knowledge, the first collaborative autoethnography of an archaeological survey in a video game, reflecting on our recorded footage, notes and data. Through a diffractive analysis, we demonstrate the value of video game archaeology as a form of hauntological practice that allows for a deeper reflection on the knowledge production process, and in doing so contribute to the development of new interdisciplinary methodologies in HCI, archaeology and games research.

The use of AI in product design during early creative phases raises questions about its long-term consequences. Concerns are that extended AI use might inhibit creative cognitive processes, especially in novice designers. The aim of this study is to contribute to ongoing research in creative cognition and creative support tools such as AI in design. We conducted an exploratory study with 61 undergraduate students to analyze design exploration in sketching versus AI concept generation. The results indicate that AI groups produced a higher quantity and variation of total ideas (including text-based ideas), while sketch groups generated more image-based ideas. It was inconclusive whether the final image concepts from both AI and sketch groups were more creative. Additionally, homogenization effects were observed in the AI groups. Moreover, while the evolution of the design intent was evident in students who sketched, the focus in AI groups appeared to shift towards the tool (AI), which we analyzed as different design space exploration (DSE) prompting styles.

The call for novel approaches in participatory design (PD) and co-design (CD) as well as in educational settings has become louder in recent years, especially when it comes to considerations of empowerment and inclusion of marginalized perspectives. Co-designing edularps (educational live-action roleplaying games) is an innovative approach that could be used in both settings. This paper reports on the combination of three studies carried out in an educational context focusing on design thinking. Findings include indications that through co-designing edularps cooperation and creativity can be practiced, and empowerment and intrinsic motivation can be experienced. Cooperation, creativity, and empowerment are essential aspects in PD and CD as well as in education for future skills and design thinking. Intrinsic motivation is relevant in educational settings since it correlates with successful learning. This paper focuses on an evaluative examination of how co-design of edularps influences the practice and fostering of creativity, collaboration, empowerment, and intrinsic motivation. Based on the findings, incorporating edularp co-design into the repertoire of tools used in PD, CD, and educational settings is recommended.

Fog screens are a projection medium for mid-air graphics, they are see-through and reach-through. Fog screens are traditionally generated by laminar flows coming out of linear outlets and thus are usually static. Here, we show that ultrasonic beams create a streaming field of constrained airflow that direct aerosols in a fast and controllable way. We characterize various aerosols under streaming and optical diffusion, and evaluate control methods for obtaining different aerosol shapes. Aerosol columns are raised, moved and pushed in a few hundred milliseconds to serve as a projection medium. Hands and other objects do not disturb the fog columns significantly, allowing for direct interaction. We showcase applications by projecting on multiple columns that can be moved continuously within the display volume, reach-through interactions and mixed-reality for tabletop games.

Digital flavour modulation represents a significant research challenge within Human-Food Interaction. Previous work has focused on modulating basic tastes, while the modulation of trigeminal sensations such as spiciness and coolness remains underexplored. Spicy and cool substances contribute substantially to the sensory appeal of food and beverages; however, their overconsumption can have adverse health effects. To enhance these trigeminal flavours without chemical additives, this study proposes an integrated multimodal approach combining electrical tongue stimulation with congruent olfactory stimuli. Unlike unimodal methods, our approach leverages the interaction between direct neural stimulation and olfactory integration to selectively modulate distinct spiciness and coolness perception. Psychophysical experiments demonstrated that our method significantly enhanced perceived coolness through combination of electrical tongue stimulation and lemon odor, and significantly enhanced perceived spiciness of a spicy solution by electrical tongue stimulation. These findings suggest that our method expands design space for digital flavour modulation and contributes to healthier and more enriched eating and drinking experiences.

While memes enhance social interaction on social media, they can raise privacy and security concerns. Despite research on overtly toxic or unsafe memes, little attention has been given to users' experiences with seemingly safe memes and how contextual factors trigger privacy concerns. This study explores users’ comfort levels, influencing factors, underlying reasons for discomfort, and unmet needs when engaging with such memes. We first collected and analyzed 2,317 Reddit posts describing real-world meme experiences, then conducted an online survey with 324 participants to evaluate comfort across curated scenarios. Our findings reveal that perceived-safe memes can cause harm when shared inappropriately, with comfort shaped by content and context. Privacy concerns intensify with deeper involvement, strangers, and sensitive meme topics. We identified users' desire for consent and control in meme interactions. Based on our study, we make recommendations for users, developers of social media platforms and policymakers to address meme-related privacy and contextual concerns.

People often have things they want to say but hold back in conversations, fearing being vulnerable or facing social consequences. Online, this restraint can take a distinctive form: even when such thoughts are written out - in moments of anger, guilt, or longing - people may choose to withhold them, leaving them unsent. This process is underexamined; we investigate the experience of writing such messages within people's digital communications. We find that unsent messages become expressive containers for suppressed feelings, where the act of writing creates a pause for reflection on the relationship and oneself. Building on these insights, we probed into how the design of the writing platforms of unsent messages affects people's experiences and motivations. Speculating with participants on nine evocative variants of a note-taking platform, we highlight how design shapes the emotional, temporal, and ritualistic qualities of unsent messages, revealing tensions between people's social desires and communicative actions.

The absence of physical information during hand-object interaction in a virtual environment diminishes realism and immersion. Kinesthetic haptic feedback has proven effective in delivering realistic object-derived haptic cues, enhancing the overall virtual reality (VR) experience. Here, we propose kinesthetic illusion through a novel application of finger tendon vibration (FTV), which creates an illusory sensation of finger movement. To effectively apply FTV for virtual object interactions, we first examine the effects of short-duration FTV (<5 s) through 3 perception studies. Based on study results, we design 6 exemplary VR scenarios, representing the overall design space of VR object interactions, and 4 different haptic rendering strategies for FTV. We evaluated these rendering methods on each VR scenario and derived a design guideline for FTV application. We then compared FTV with no vibration and simple vibration, observing that FTV enhances VR experience by providing realistic resistance on the finger, greatly improving body ownership.

People speak aloud to externalize thoughts as one way to help clarify and organize them. Although Speech-to-text can capture these thoughts, transcripts can be difficult to read and make sense due to disfluencies, repetitions and potential disorganization. To support thinking through verbalization, we introduce ORALITY, which extracts key information from spoken content, performs semantic analysis through LLMs to form a node-link diagram in an interactive canvas. Instead of reading and working with transcripts, users could manipulate clusters of nodes and give verbal instructions to re-extract and organize the content in other ways. It also provides AI-generated inspirational questions and detection of logical conflicts. We conducted a lab study with twelve participants comparing ORALITY against speech interaction with ChatGPT. We found that ORALITY can better support users in clarifying and developing their thoughts. The findings also identified the affordances of both graphical and conversational thought clarification tools and derived design implications.

Deceptive/Manipulative Patterns (DMP) are interface designs, also known as "dark patterns," that manipulate user behavior. While considerable attention has been paid to their ethical and legal implications, empirical evidence about their real-world effects remains diffuse. This review synthesizes up-to-date experimental studies, focusing on works that quantify how (or whether) DMPs influence users. We also aggregate findings on interventions aimed at reducing DMP effects. Our synthesis highlights the experimental agreement that DMPs do significantly alter user behavior (with large variance in effect size) and that external interventions have been mostly unsuccessful in mitigating their effects. Lastly, we show that significant correlations between DMP effects and personal characteristics (e.g., age or political affiliation) are uncommon, indicating DMPs similarly affected nearly all populations tested. By summarizing the experimental evidence, we clarify the effects of DMPs, highlight gaps and tensions in the existing experimental literature, and help inform ongoing research and policy directions.

Knowing what collaborators attend to is essential. Previous studies demonstrated that shared gaze enhances coordination and social connectedness in remote settings. In collocated settings, gaze can be both naturally observable and technologically augmented. AR enables gaze cues to be rendered explicitly in the environment. To investigate if and how such cues are beneficial in collocated AR collaboration, we examined both qualitative and quantitative effects across three task types (puzzle, negotiation, search) and two spatial setups (plane, room), focusing on task completion time and the collaborative experience. In our user study with 24 dyads (n=48), we varied gaze visibility and measured task performance, user preference, social connectedness, and shared attention. Our results show that sharing gaze in collocated collaborative AR can increase shared attention, is perceived as helpful, and improves the user experience, similar to remote collaboration, but has a limited impact on the actual task completion time across the chosen tasks.

The integration of generative artificial intelligence (GenAI) into design processes raises fundamental questions about behavioral patterns in human-GenAI interaction. This study examines how 16 professional designers interact with GenAI tools during concept development through a mixed-methods approach including pre/post-task questionnaires, video-based behavior analysis, and digital interaction tracking. Results reveal a critical distinction between reflective usage modes and creative modes, with differentiated cognitive impacts. Analysis of communication loops shows significant correlations between interaction difficulties and final design output quality. Three distinct clusters emerge: designers with fluid, problematic, and adaptive interaction patterns. By providing a methodological framework for evaluating GenAI tool effectiveness in design practice, this research contributes to theoretical understanding of behavioral processes in human-GenAI co-creation. Findings reveal specific strategies and workflow adaptations that optimize designer-GenAI collaboration, informing both design methodology and human-computer interaction practice.

Videoconference conversations about data often entail screen sharing visualization artifacts, in which nonverbal communication goes largely ignored. Beyond presentation use cases, conversations supported by visualization also arise in collaborative decision making, technical interviews, and tutoring: use cases that benefit from participants being able to see one another as they exchange questions about the data. In this paper, we employ a reciprocal compositing of visualization and interface widgets over the mirrored video of one's conversation partner, suggestive of a pane of glass, in which both parties can simultaneously manipulate composited elements via bimanual gestures. We demonstrate our approach with implementations of several visualization interfaces spanning the aforementioned use cases, and we evaluate our approach in a study (N = 16) comparing it to videoconferencing while using a mouse to interact with a collaborative web application. Our findings suggest that our approach promotes feelings of presence and mutual awareness of analytical intent.

Shaking a cup of wine or other fluids in virtual environments is engaging but has been limited by challenges in delivering real-time haptic feedback for liquid collisions. ShakeSense is a haptic rendering system that integrates electrotactile stimulation with physics-based simulation to deliver immersive feedback for liquid dynamics in handheld containers. It employs a high-density electrode array to deliver dynamic tactile sensations, conveying friction and pressure changes on the user's fingerpad. A dedicated end-to-end pipeline computes fingerpad forces from liquid-container-finger interactions, ensuring feedback aligns with natural fluid movement. Two studies evaluated ShakeSense’s performance and user perception. Study 1 showed that electrotactile patterns were distinguishable across directions, and synchronizing container movement with stimulation enhanced perceived force changes. Study 2 demonstrated that ShakeSense effectively simulated liquid motion, capturing multidimensional, coordinated interactions, and outperformed conventional Center-of-Mass approaches. Overall, ShakeSense provides clear, fine-grained tactile feedback for fluid interactions.

Adolescence is marked by strong creative impulses but limited strategies for structured expression, often leading to frustration or disengagement. While generative AI lowers technical barriers and delivers efficient outputs, its role in fostering adolescents’ expressive growth has been overlooked. We propose MusicScaffold, an adolescent-centered framework that transforms classical AI roles from broad conceptualizations into stage-specific, actionable developmental scaffolds designed to make expressive strategies transparent and learnable and to support adolescents in mastering creative expression. In a four-week study with middle school students (ages 12–14), MusicScaffold enhanced cognitive specificity, behavioral regulation, and affective autonomy in music creation. By reframing generative AI as a scaffold rather than a generator, this work bridges the machine efficiency of generative systems with human growth in adolescent creativity education.

Recent advances in material-centric personal fabrication have enabled the use of custom inks and paints with functional properties to create free-form displays. However, working with these materials, such as through airbrushing, remains a skill-intensive process that limits non-specialist access, adoption, and further development. To address these challenges, we developed Dispray, an AR-augmented airbrush tool for fabricating electroluminescent displays. The tool was shaped by insights from a study with artists and engineers and refined through iterative prototyping. We evaluated Dispray by re-engaging with the original artists and engineers and conducting a follow-up study with novice users, demonstrating its effectiveness in supporting both skill acquisition and functional fabrication. This work contributes a novel approach to connecting emerging material fabrication with accessible, user-centered tools, advancing the democratisation of interactive device creation.

Large Language Models (LLMs) hold promise in supporting creative writing, yet the role of proactive AI in collaborative writing remains underexplored due to concerns around human agency and disruption. To investigate effective strategies for proactive AI support, we conducted a Wizard-of-Oz study simulating two suggestion styles: intrusive suggestions (next-sentence completions) and non-intrusive suggestions (exploratory proposals), where participants completed two story outlining tasks under each style, receiving real-time proactive suggestions from a human wizard acting as the AI. Both quantitative and qualitative results show that proactive AI can enhance creativity and accelerate writing. However, we observed a trade-off between AI involvement and perceived human agency. This trade-off was moderated by how strongly AI stimulated users—greater inspiration led to stronger perceived agency even under high AI involvement. Based on wizards' behavior, we offer guidance on suggestion style and timing to better balance creativity and agency for future proactive AI writing systems.

Web-based activities span multiple webpages. However, conventional browsers with stacks of tabs cannot support operating and synthesizing large volumes of information across pages. While recent AI systems enable fully automated web browsing and information synthesis, they often diminish user agency and hinder contextual understanding. We explore how AI could instead augment user interactions with content across webpages and mitigate cognitive and manual efforts. Through literature on information tasks and web browsing challenges, and an iterative design process, we present novel interactions with our prototype web browser, Orca. Leveraging AI, Orca supports user-driven exploration, operation, organization, and synthesis of web content at scale. To enable browsing at scale, webpages are treated as malleable materials that humans and AI can collaboratively manipulate and compose into a malleable, dynamic, and browser-level workspace. Our evaluation revealed an increased "appetite" for information foraging, enhanced control, and more flexible sensemaking across a broader web information landscape.

We explore new interactions for wayfinding in complex, hazardous environments through the concrete case of multi-pitch rock climbing. Working with seven expert climbers, we derived design principles for navigation tools that support both pre-climb planning and on-the-wall decision making with limited physical and mental bandwidth. We then demonstrate these principles in practice through the creation of a mobile application that incorporates high-fidelity vertical terrain models, spatially-anchored multi-modal annotations, integrated human-scale avatars, and adaptable one-handed interactions. Based on our expert feedback and experiences developing the tool, as well as results from a 3-week public deployment and responses from 16 climbers, we highlight new opportunities for interactive tools for rock climbing as well as other hazardous, high-focus activities.

It has been suggested that the functional significance learners ascribe to virtual rewards in gamified systems can have a significant impact on intrinsic motivation. Yet, to date, there has been a lack of research examining this relationship empirically. In the present study, we therefore applied Cognitive Evaluation Theory to examine how learners’ (n = 162) interpretation of virtual rewards in Duolingo affected autonomy satisfaction, competence satisfaction, and intrinsic motivation. Based on a structural equation modeling approach, our findings suggests that the informational significance learners ascribe to virtual rewards positively affects competence satisfaction, and that autonomy and competence satisfaction together affect intrinsic motivation. For the HCI field, the results point towards the importance of moving beyond treating virtual rewards in gamified learning as a use-or-avoid decision, and instead consider how such design elements can be modified to provide increased encouragement and positive feedback.

Exergames promise enjoyable physical activity through gameplay, yet players often face barriers that undermine engagement, safety, and retention. To date, knowledge about which barriers are encountered by end-users of commercial exergames and which mitigation strategies are used is limited. To address this gap, we conducted an online survey with 174 participants and provide a comprehensive organization of 60 reported barriers across six categories: physical, mental, social, environmental, technological, and game design. Key barriers include space limitations, social discomfort, addictive gameplay, and injuries. Our analysis reveals that while players try to mitigate barriers through ad-hoc strategies, issues like embarrassment, addiction, and harassment remain difficult to overcome. These findings highlight the need for more adaptive game designs, including dynamic spatial adjustments, personalized pacing mechanisms, and supportive social features. This work advances the understanding of exergame barriers and their impact and offers actionable insights for designing more inclusive and resilient movement-based games.

We present a new and accurate approach for gaze estimation on consumer computing devices. We take advantage of continued strides in the quality of user-facing cameras found in e.g., smartphones, laptops, and desktops — 4K or greater in high-end devices — such that it is now possible to capture the 2D reflection of a device's screen in the user's eyes. This alone is insufficient for accurate gaze tracking due to the near-infinite variety of screen content. Crucially, however, the device knows what is being displayed on its own screen — in this work, we show this information allows for robust segmentation of the reflection, the location and size of which encodes the user's screen-relative gaze target. We explore several strategies to leverage this useful signal, quantifying performance in a user study. Our best performing model reduces mean tracking error by ~18% compared to a baseline appearance-based model. A supplemental study reveals an additional 10-20% improvement if the gaze-tracking camera is located at the bottom of the device.

As LLM-based Conversational Avatars increasingly act as collaborators in hybrid indoor navigation, understanding how their personality traits influence human-avatar proxemic behavior is becoming crucial. Prior work has largely examined personality effects in static or one-sided interactions such as sitting, standing, or approaching. However, there is a gap in research on how avatar personality and motion-related factors (e.g., walking speed) shape proxemics when both the human and avatar are in motion. To address this, we developed an AR indoor navigation system featuring a Conversational Virtual Avatar (CVA) with three distinct personalities: Dominant, Warm, and Conscientious. The CVA guides users to destinations within the environment. In a between-subjects study ($N$=27), we found statistically significant effects of avatar personality and walking speed on proxemic behavior. Our work contributes to a broader understanding of the role of personality and walking speed of a CVA on human-avatar proxemic behaviour during navigation.

This paper looks at texture---middle-level components---as an important aspect of drawing. We present a hardware tool, penPal, that is designed to support dynamic mark-making and direct creative actions at this level. By incorporating a tendon-driven continuum robot, penPal’s tip can move independently, giving the user a new axis of creative control. Combined with the user’s own manipulations, penPal allows for emergent combinations of computer and manual control over the rapid generation of diverse textures. Through a 10-participant study and a professional artist commission, we examine how users negotiate control by integrating multiple coordinate systems (their body, the paper, and penPal’s tip) as they construct compositions. We suggest some benefits of supporting users at the texture level, such as the ability to shift the primary focus of their activity, the ability to selectively defamiliarize the creative process for generative potential, and for pleasure.

While generative AI tools are increasingly adopted for creative and analytical tasks, their role in interpretive practices,where meaning is subjective, plural, and non-causal, remains poorly understood. This paper examines AI-assisted tarot reading, a divinatory practice in which users pose a query, draw cards through a randomized process, and ask AI systems to interpret the resulting symbols. Drawing on interviews with tarot practitioners and Hartmut Rosa's Theory of Resonance, we investigate how users seek, negotiate, and evaluate resonant interpretations in a context where no causal relationship exists between the query and the data being interpreted. We identify distinct ways practitioners incorporate AI into their interpretive workflows, including using AI to navigate uncertainty and self-doubt, explore alternative perspectives, and streamline or extend existing divinatory practices. Based on these findings, we offer design recommendations for AI systems that support interpretive meaning-making without collapsing ambiguity or foreclosing user agency.

Silent, eyes-free text entry remains challenging when speech and touch are impractical. Prior wearable systems required custom sensors or limited users to a small vocabulary. We present MorsEar, an IMU-only earable framework that maps near-ear micro-gestures such as taps for dot/dash; slide/pull/circle for space/delete/send, into character-level Morse, enabling unrestricted composition with a compact lexicon for lightweight on-device autocorrect. The result is a low-bandwidth, reduced-exposure communication channel that works eyes-free and voice-free in accessibility scenarios, silent zones, and constrained environments. MorsEar infers words using a physics-aware preprocessing stack and a compact CNN, feeding a tempo-adaptive segmentation with rolling buffers; an on-device decoder provides real-time feedback entirely on-phone. In a 24-participant study (with four accessibility users) across Silent, Cafe, and Metro, MorsEar achieved CER 7.3% and WER 12.5% → 7.8% (Autocorrect), with median WPM of 9.3/9.1/5.8, respectively. Similar to other accessibility-oriented encodings such as Braille, Morse requires a brief familiarization period to learn the timing and rhythm of dots and dashes; after which, MorsEar shows that commodity earable IMUs can support discreet, low-exposure text entry that scales beyond discrete commands to language-level interaction.

HCI research increasingly engages with relational notions of ethics, such as care, felt and transcorporeal ethics, as new paradigms for design. Here, we discuss these relational notions in the context of multispecies design, extending it to incorporate Acampora’s concept of Corporal Compassion, which grounds ethics on a shared sense of livingness and vulnerabilities across beings. In order to elicit corporal compassion towards microorganisms, we designed a dining-theatre intervention, which invited participants to ingest and assign moral values to dishes prepared with speculative human-microbial hybrid cells originated from beings exposed to similar levels of bodily distress. Tried with 47 participants in 7 sessions, the work surfaced the idiosyncrasies behind participants’ moral frameworks, and how socialised prescriptive frameworks of ethics sometimes acted as closure towards relational approaches. We discuss how HCI could rethink traditional frameworks of ethics in ways that support relationality, while calling for researchers to make space for moral hesitation.

Frustration in games can have negative consequences for both players and those around them. Despite these effects, methods for supporting frustration management in hectic gameplay are scarce. In this paper, we present Frustration Buddy, a novel tangible intervention system aimed at managing frustration during play. Frustration Buddy leverages distraction and soothing techniques to help players control their emotions. Our paper provides an artifact contribution, complemented by exploratory findings from semi-structured interviews with nine participants on frustration in games, how they manage it, and their opinions on Frustration Buddy’s design and applicability in their gaming environments. The results suggest participants were open to the idea of a device supporting frustration management and that the use of a tangible device like a stress ball was well-received. We provide insights on how to design such a device based on our design decisions and the preferences expressed by the gamers in our interviews.

Dialect bias is pervasive yet often unconscious, normalized, or obscured by masking. Existing HCI interventions primarily audit disparities and propose reactive fixes. We present CompassioMate, a dialect-aware serious game that nurtures perspective-taking through AI-mediated play. Players listen to audio samples to identify regional dialects, engage in simulated social interactions involving dialect discrimination, and explore branching narratives that reveal how changes in wording or stance can influence the outcomes. In a three-week field study with 20 university students, participants reported feeling comfortable when observing region-tailored dialogues; several described experiencing perspective change. We contribute: 1) a formative study identifying goals for safe action consequence modelling, 2) the design and evaluation of a serious game integrating dialect audio, region-mapping play, bias; and 3) design implications highlighting listener-side training, transparent evaluation, and narratives maintaining psychological well-being.

While many modern gaming environments provide haptic feedback, laptop keyboard gaming remains largely without rich tactile interaction, despite a rapidly growing audience. In this paper, we propose the HapPalm interface, a novel laptop interface concept that delivers rich spatio-temporal vibrotactile feedback through the palmrest area, allowing players to feel game events with their palms. Our prototype uses dual 4×6 linear resonant actuator arrays. To render various game events with the HapPalm interface, our first study aims to create a haptic pattern dataset. Iterative design workshops identified 11 haptic pattern templates, of which our second study validated that they convincingly convey diverse game events. Our final study embedded these patterns into a custom game, showing that spatial haptics significantly improved fun, immersion, realism, and presence compared to non-spatial or no-haptic conditions. HapPalm interface demonstrates that palmrest-based haptics can enrich keyboard-only laptop gaming, providing an expressive and immersive tactile channel for future laptop interfaces.

As eye-tracking becomes increasingly common in modern mobile devices, the potential for hands-free, gaze-based interaction grows, but current gesture sets are largely expert-designed and often misaligned with how users naturally move their eyes. To address this gap, we introduce a two-phase methodology for developing intuitive gaze gestures. First, four co-design workshops with 20 non-expert participants generated 102 initial concepts. Next, four gaze interaction experts reviewed and refined these into a set of 32 gestures. We found that non-experts, after a brief introduction, intuitively anchor gestures in familiar metaphors and develop a compositional grammar; i.e., activation (dwell) + action (gaze gesture or blink), to ensure intentionality and mitigate the classic Midas Touch problem. Experts prioritized gestures that are ergonomically sound, aligned with natural saccades, and reliably distinguishable. The resulting user-grounded, expert-validated gesture set, along with actionable design principles, provides a foundation for developing intuitive, hands-free interfaces for gaze-enabled devices.

\textit{What if future dining involved eating robots?} We explore this question through a playful and poetic experiential dinner theater: a tangible design fiction staged as a 2052 Paris restaurant where diners consume a biohybrid flying robot in place of the banned delicacy of ortolan bunting. Moving beyond textual or visual speculation, our “dinner-in-the-drama” combined performance, ritual, and multisensory immersion to provoke reflection on sustainability, ethics, and cultural identity. Six participants from creative industries engaged as diners and role-players, responding with curiosity, discomfort, and philosophical debate. They imagined biohybrids as both plausible and unsettling—raising questions of sentience, symbolism, and technology adoption that extend beyond conventional sustainability framings of synthetic meat. Our contributions to HCI are threefold: (i) a speculative artifact that stages robots as food, (ii) empirical insights into how people negotiate cultural and ethical boundaries in post-natural eating, and (iii) a methodological advance in embodied, multisensory design fiction.

We investigate how the presence and type of interaction context shapes sycophancy in LLMs. While real-world interactions allow models to mirror a user's values, preferences, and self-image, prior work often studies sycophancy in zero-shot settings devoid of context. Using two weeks of interaction context from 38 users, we evaluate two forms of sycophancy: (1) agreement sycophancy -- the tendency of models to produce overly affirmative responses, and (2) perspective sycophancy -- the extent to which models reflect a user's viewpoint. Agreement sycophancy tends to increase with the \textit{presence} of user context, though model behavior varies based on the context \textit{type}. User memory profiles are associated with the largest increases in agreement sycophancy (e.g. +45% for Gemini 2.5 Pro), and some models become more sycophantic even with non-user synthetic contexts (e.g. +15% for Llama 4 Scout). Perspective sycophancy increases only when models can accurately infer user viewpoints from interaction context. Overall, context shapes sycophancy in heterogeneous ways, underscoring the need for evaluations grounded in real-world interactions and raising questions for system design around alignment, memory, and personalization.

Teenage years are a critical period for shaping food practices and health behaviors, yet teens remain underrepresented in research on future food and health technologies. This paper reports on design fiction workshops where 20 teens speculated on artifacts such as health-tracking mirrors and food-making machines while reflecting on their eating habits and values. Our analysis shows how teens negotiate their human stances in a techno-centric world, balancing excitement about innovation with concerns over health, control, and responsibility. We contribute to HCI by: (1) identifying teen-specific design considerations for reflective healthy-eating technologies, highlighting “absence” as a protective affordance; (2) reframing food technologies for teens as sites of family care and playful identity work, opening a design space at the intersection of reflection and play; and (3) advancing methodological understanding of youth-centered design fiction by showing how dual-mode speculative workshops can move teen participants beyond solutionist or anti-solutionist positions toward grounded negotiation with sociotechnical systems.

Vocal training is difficult because the muscles that control pitch, resonance, and phonation are internal and invisible to learners. This paper investigates how Electromyography (EMG) and ultrasonic imaging (UI) can make these muscles observable for training purposes. We report three studies. First, we analyze the EMG and UI data from 16 singers (beginners, experienced \& professionals), revealing differences among three vocal groups of the muscle control proficiency. Second, we use the collected data to create a system that visualizes an expert's muscle activity as reference. This system is tested in a user study with 12 novices, showing that EMG highlighted muscle activation nuances, while UI provided insights into vocal cord length and dynamics. Third, to compare our approach to traditional methods (audio analysis and coach instructions), we conducted a focus group study with 15 experienced singers. Our results suggest that EMG is promising for improving vocal skill development and enhancing feedback systems. We conclude the paper with a detailed comparison of the analyzed modalities (EMG, UI and traditional methods), resulting in recommendations to improve vocal muscle training systems.

Multimodal interaction has long promised to make interfaces more intuitive and effective by combining complementary inputs. Among these, gaze and speech form a compelling pairing: gaze provides rapid spatial grounding, while speech conveys rich semantic information. Together, they offer rich cues for understanding user behaviour and intent. Yet despite decades of exploration, the research remains fragmented, making this synthesis timely as these inputs mature and are integrated into consumer-ready devices. This scoping review examined 103 studies published between 1991 and 2025, organised into \emph{explicit}, where users intentionally provide gaze and speech, and \emph{implicit}, where systems leverage users' natural behaviours to support interaction. Across both, we identified recurring ways for combining gaze and speech to resolve ambiguity, ground references, and support adaptivity. We contribute a synthesis of research on their combined use while highlighting challenges of temporal alignment, fusion and privacy, offering guidance for future research toward richer multimodal human-computer interaction.

Creating compelling 3D character animations typically requires either expert use of professional software or expensive motion capture systems operated by skilled actors. We present DancingBox, a lightweight, vision-based system that makes motion capture accessible to novices by reimagining the process as digital puppetry. Instead of tracking precise human motions, DancingBox captures the approximate movements of everyday objects manipulated by users with a single webcam. These coarse proxy motions are then refined into realistic character animations by conditioning a generative motion model on bounding-box representations, enriched with human motion priors learned from large-scale datasets. To overcome the lack of paired proxy–animation data, we synthesize training pairs by converting existing motion capture sequences into proxy representations. A user study demonstrates that DancingBox enables intuitive and creative character animation using diverse proxies, from plush toys to bananas, lowering the barrier to entry for novice animators.

Given the growing prevalence of fake information, including increasingly realistic AI-generated news, there is an urgent need to train people to better evaluate and detect misinformation. While interactions with AI have been shown to durably reduce people's beliefs in false information, it is unclear whether these interactions also teach people the skills to discern false information themselves. We conducted a month-long study where 67 participants classified news headline-image pairs as real or fake, discussed their assessments with an AI system, followed by an unassisted evaluation of unseen news items to measure accuracy before, during, and after AI assistance. While AI assistance produced immediate improvements during AI-assisted sessions (+21\% average), participants' unassisted performance on new items declined significantly by 15.3\% in week 4 compared to week 0. These results indicate that while AI may help immediately, it may ultimately degrade long-term misinformation detection abilities.

While Personal Informatics (PI) systems support behavior change, everyday well-being involves more than achieving individual target behaviors. It is shaped by cultural narratives that give actions meaning. In South Korea, the God-Saeng (God生) phenomenon—encompassing disciplined, collective, and publicly documented self-improvement practices—offers a lens into how well-being is negotiated in daily life. We conducted a 10-day probe (N=24) with bite-sized missions to examine how young adults engaged in God-Saeng. Participants relied on planning practices, accountability infrastructures, and datafication to stabilize themselves, yet these same routines also intensified pressures toward self-monitoring and performance. They navigated tensions between consistency and flexibility, authenticity and visibility, and productivity and broader values such as relationships, and reinterpreted ordinary activities through sociocultural contexts. These insights suggest design opportunities for PI systems that move beyond tracking, toward digital instruments that help users negotiate tensions, make meaning, and reflexively understand how technologies participate in their culturally and existentially situated well-being.