注目の論文一覧

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.

Role-playing games allow players to explore a digital world through a character's eyes. For minority groups, such as queer players, representation is not a given when playing popular role-playing games. We surveyed a diverse sample of 464 queer and non-queer players and followed up with 31 in-depth interviews. We asked players about their perspectives on their characters' gender and sexual orientation. The quantitative results showed that cisgender men were the least likely group to find gender representation important and heterosexual players were least likely to consider the representation of sexual orientation as important. However, following up with a thematic analysis, we note many nuances and within-group differences. We identify four themes of how players of all identities view character creation—the character as a shield, a guide, a portrayal, and a creation—and discuss how digital games can improve character design and character creation options.

Hybrid meetings are the new reality, yet they lack the richness of face-to-face interaction. In shared spaces, virtual or physical, interaction relies on more than words: proximity, non-verbal cues, and subtle movements all shape communication. Proximity captures how close we stand, where we face, and how we move around others. This paper investigates how proxemics in dyad and triad conversations translate across physical and virtual contexts. We conducted a study with 24 participants in four groups, completing social tasks under four conditions: face-to-face, co-located XR, remote XR, and hybrid XR. Our instrumentation of physical and virtual environments enables direct comparison. The work contributes a rich open dataset of 2.3 million rows across 32 columns, supporting comparative and replicable analysis. This is the first study to compare proxemics across face-to-face, co-located XR, remote XR, and hybrid XR, offering a foundation for understanding how social space translates across contexts.

Mid-air handwriting is a freeform text input modality that enables expression of individuality and creativity. In Mixed Reality, the recognition of writing strokes has conventionally depended on manual action or proximal planes. Such explicit reliance imposes cognitive load and quickly leads to fatigue. We present InkFlow, a novel bare-hand handwriting interaction approach that enables users to write continuously and naturally without explicit stroke control. We first design a user-friendly pipeline that leverages the widely adopted pinch–release gesture to intuitively collect annotated handwriting data. Next, we enhance a lightweight DS-TCN model with boundary-aware strategy to improve the learning of kinematic features. Moreover, building on cross-domain meta-learning, our approach achieves effective cross-user generalization and supports rapid personalization for new users. The comparative user study (N=30) shows the effectiveness and usability of our method and interaction design. A closed-loop online study (N=12) further demonstrates notable improvements in handwriting efficiency and physical comfort.

Sketch-to-image systems let users transform simple line drawings into realistic images, but current workflows force users into tedious redraw-regenerate cycles that slow creative exploration. We introduce two complementary interaction techniques that reduce iteration friction: AutoSketch, which extends partial sketches through AI-driven completions (pre-generation support), and BackSketch, which transforms generated images back into editable sketches at multiple abstraction levels (post-generation support). In a study with 30 participants, the results indicate that both techniques can improve exploration and expressiveness compared to a baseline sketch-to-image system, while AutoSketch also can increase users’ sense of agency and co-creation with the AI. We contribute new evidence that shifting support before or after generation opens distinct pathways for balancing user control and system initiative. Together, our results establish pre- and post-generation assistance as a design space for co-creative sketch-to-image systems.

Researchers can build craft-aligned digital fabrication technologies by designing interfaces inspired by craft tools. This process often demands real-time physical interactions not supported by today’s automation-focused CNC control systems. We theorize we can lower engineering challenges for craft-aligned CNC prototyping by allowing designers to modify existing CNCs to support both automated and real-time control. We contribute a new creative motion control system, Stepdance, which consists of two elements: 1) modular controllers that replace the G-code controller of a CNC and can be chained together to develop new interfaces, and 2) a modular programming library that supports declarative mappings between live user input, pre-programmed operations, and machine motion. We developed Stepdance with practitioners at the Haystack Mountain School of Craft, where we used the system to modify commercial plotters and 3D printers. We analyze the resulting artifacts, interactions, and ideas to discuss how Stepdance can broaden the practice of CNC design via physical metaphor.

Toxic behavior is a problem in online gaming platforms such as League of Legends (LoL), undermining player well-being and fairness. Platforms increasingly optimize “engagement” without distinguishing between positive and negative participation. Drawing on dual-process theory, we ask when hostile interactions can become economically productive. In an explanatory sequential mixed-methods study with LoL players, Study 1 (N = 430) models how reflective, System~2 brand bonds (i.e., brand personality, brand involvement, brand engagement) and negatively valenced, System~1 reactive responses (self-reported toxic behavior) relate to in-game spending. Study 2 (N = 80) uses reflexive thematic analysis to show how players interpret, repair, and channel frustration and hostility through cosmetics, events, and progression systems. Across studies, toxic behavior is positively associated with self-reported purchases and partially transmits the association between reflective brand attachments and spending. We contribute a dual-pathways account of how governance and monetization infrastructures can fold harmful engagement into value extraction, and we outline critical design provocations for centrally governed, highly monetized platforms.

Virtual Reality (VR) offers portable and flexible workspaces. However, enabling efficient and comfortable interactions without external input devices remains challenging. We propose leveraging redirected input to enable comfortable and touch-like interaction for quick and intuitive control. Our design study revealed that while touch interaction performs well with direct input, its performance degrades significantly under input redirection. In contrast, using pinch improves redirected input by providing self-haptic feedback and reducing input dimensionality, thereby compensating for spatial discrepancies. Based on these findings, we introduce Redirected Pinch, a bare-hand interaction technique that combines input redirection with pinch confirmation. It creates a virtual plane at waist height, remapping hand movements on the plane to a vertical window, with pinch gestures used for confirmation. A user study demonstrated that Redirected Pinch achieves a strong balance of accuracy, efficiency, comfort, and sense of agency across fundamental interactions.

Perceptual grouping enables people to organize elements into units according to intrinsic (e.g., proximity) and extrinsic (e.g., common region) principles. However, the role of physical surfaces as extrinsic grouping cues for virtual elements in Augmented Reality (AR) remains unclear. To provide a deeper understanding, we conducted two within-subject studies. The first study (N = 24) using repetition discrimination tasks revealed that surfaces can be common-region cues in 3D, with their influence depending on their distance to target objects along the viewing direction. Building on these findings, the second study (N = 24) employed both objective and subjective measures to capture the interaction between proximity and common-region cues in AR. Results indicate that competing cues reduce group clarity. They also enable us to distill people's strategies for improving the clarity by leveraging their physical and virtual environments. Finally, we propose design recommendations for future AR systems in assisted grouping tasks.

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.

Sketching provides an intuitive way to convey dynamic intent in animation authoring (i.e., how elements change over time and space), making it a natural medium for automatic content creation. Yet existing approaches often constrain sketches to fixed command tokens or predefined visual forms, overlooking their free-form nature and the central role of humans in shaping intention. To address this, we introduce an interaction paradigm where users convey dynamic intent to a vision–language model via free-form sketching, instantiated here in a sketch storyboard to motion graphics workflow. We implement an interface and improve it through a three-stage study with 24 participants. The study shows how sketches convey motion with minimal input, how their inherent ambiguity requires users to be involved for clarification, and how sketches can visually guide video refinement. Our findings reveal the potential of sketch–AI interaction to bridge the gap between intention and outcome, and demonstrate its applicability to 3D animation and video generation.

One central goal of game designers is to make games that resonate with players. Yet, within HCI games research, resonance is used vaguely as an everyday notion. In this work, we draw on psychological research on resonance to conduct a qualitative survey (n = 110) to explore how players characterize game experiences that resonated with them, to deliminate what resonance means for players and the interactive medium of games. Our findings illustrate how resonance captures the feeling of gameplay encounters that go on to have profound and long-lasting emotional and cognitive impacts. Our findings outline resonance as an underlying experiential quality relevant to various existing PX conceptualizations, such as eudaimonia, meaningfulness, reflection, emotional challenge, game feel, and perspective or behavioral change. Based on our findings, we outline resonance as a useful explanatory concept for what makes videogame experiences emotional, meaningful, moving, and even transformative experiences.

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.

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.

The dissemination of scholarly research is critical, yet researchers often lack the time and skills to create engaging content for popular media such as short-form videos. To address this gap, we explore the use of generative AI to help researchers transform their academic papers into accessible video content. Informed by a formative study with science communicators and content creators (N=8), we designed PaperTok, an end-to-end system that automates the initial creative labor by generating script options and corresponding audiovisual content from a source paper. Researchers can then refine based on their preferences with further prompting. A mixed-methods user study (N=18) and crowdsourced evaluation (N=100) demonstrate that PaperTok's workflow can help researchers create engaging and informative short-form videos. We also identified the need for more fine-grained controls in the creation process. To this end, we offer implications for future generative tools that support science outreach.

Virtual Reality (VR) has been widely adopted in domains such as gaming, education, and healthcare, where 3D props play a central role in enabling immersive interaction. With the advancement of generative AI, 3D props can now be created rapidly; however, little research has explored how gestures and speech can be integrated to support prop generation. To address this gap, we introduce GestuProp, a VR prop generation system driven by co-speech gestures. Building on a formative study with 30 participants, we proposed a gesture design space and developed the VR system GestuProp. We then conducted a user study with 14 participants, which showed that GestuProp demonstrates good usability and favorable user experiences, while also revealing how object categories influence gesture use and interaction. These findings highlight the potential of gesture–speech synergy to advance prop generation in VR.

The prototyping process for e-textile circuits presents unique challenges, as traditional electronic prototyping tools are often rigid and incompatible with the flexible nature of fabric. In this paper, we document the iterative design of FabricBoards, a set of fabric-based breadboards designed for e-textile LED circuits. FabricBoards reimagine the solderless breadboard in a textile-based form, using tools and materials native to textile crafting, inviting and accessible to historically underrepresented makers. We experimented with various textile crafts including machine-sewing, felting, knitting, crocheting, digital embroidery, and weaving a breadboard. Our user study with 18 participants consisted of group workshops for ideation and individual interviews. A thematic analysis revealed four themes on the user experience of FabricBoards in terms of familiarity, materiality, and layout; the inherent incompatibility of electronic components with textiles; and the curiosity and engagement that FabricBoards evoke. Finally, we reflect with generalizable insights on computational making when reimagining e-textile breadboards.

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.

Virtual Reality (VR) enables users to engage with capabilities beyond human limitations, but it is not always obvious how to trigger these capabilities. Taking the lens of Affordance, we believe avatar design is the key to solving this issue, which ideally should communicate its capabilities and how to activate them. To understand the current practice, we selected eight capabilities across four categories and invited twelve professional designers to design avatars that communicate the capabilities and their corresponding interactions. From the resulting designs, we formed 16 guidelines to provide general and category-specific recommendations. Then, we validated these guidelines by letting two groups of twelve participants design avatars with and without guidelines. Participants rated the guidelines’ clarity and usefulness highly. External judges confirmed that avatars designed with the guidelines were more intuitive in conveying the capabilities and interaction methods. Finally, we demonstrated the applicability of the guidelines in avatar design for four VR applications.

When given the opportunity, people tend to try to reach coarse breakpoints for work interruptions. Coarse breakpoints are frequently associated with less effort when resuming the task. We investigated how supporting task resumption with augmented reality (AR)-cues affects this behavior. In a mixed factorial experiment, 50 participants performed a physical sorting task that included deferrable interruptions with varying distances to a coarse breakpoint, either with or without an AR-cue indicating the next correct step after interruption. Participants with AR-cue accepted interruptions at fine breakpoints more frequently than those without a cue, except when the coarse breakpoint was one step away, and reported less stress. Our findings indicate that AR-cues attenuate but do not eliminate the need for specific task resumption strategies, such as reaching a coarse breakpoint, and reduce the stress. Considering AR-cues for task resumption may be particularly beneficial for time-critical interruptions and fast-paced work environments.

As long as there have been digital games, there have been players who seek to modify them, using settings, mods, online resources, and other methods. Despite the long history of modification in games, research has been limited by the dichotomous values implied by players using modifications for cheating (negative) or accessibility (positive). To address these limitations, we explore game modification broadly and neutrally by surveying 167 participants about their experiences, examining how and why players modify games, effects of modification, and perceptions of ethics. The results of a qualitative analysis distill diverse player perspectives into six core findings related to playfulness, agency, connection, norms, leet-ness, and technology in modified gaming experiences, where modifications add significant value to play by enabling users to tailor games to their optimal play experience. Results highlight the diversity and morality of users, and indicate that previous understandings may be too narrow and cynical.

Extended Reality (XR) headsets enable large, reconfigurable multi-display workspaces and support view manipulation, allowing the workspace to reposition itself around the user. Cursor warping similarly reduces traversal distance and pointer search by reinitialising the cursor at defined locations. Yet when both mechanisms operate together, the spatial relationship between user, displays, and cursor becomes dynamic, and it remains unclear how cursor repositioning behaves when the workspace itself moves. In a study (N=20) of five cursor-warping strategies with two view manipulations, we show that the benefits of both do not automatically combine: workspace motion can disrupt spatial consistency and alter both performance and movement costs. We show that continuous cursor movement in world space is limited compared to alternative warping techniques, and cursor behaviour and view control are tightly coupled. Hence, cursor initialisation and view manipulation must be co-designed to support efficient and comfortable interaction in XR multi-display environments.

Mixed Reality (MR) interfaces increasingly rely on gaze for interaction, yet distinguishing visual attention from intentional action remains difficult, leading to the Midas Touch problem. Existing solutions require explicit confirmations, while brain–computer interfaces may provide an implicit marker of intention using Stimulus-Preceding Negativity (SPN). We investigated how Intention (Select vs. Observe) and Feedback (With vs. Without) modulate SPN during gaze-based MR interactions. During realistic selection tasks, we acquired EEG and eye-tracking data from 28 participants.SPN was robustly elicited and sensitive to both factors: observation without feedback produced the strongest amplitudes, while intention to select and expectation of feedback reduced activity, suggesting SPN reflects anticipatory uncertainty rather than motor preparation. Complementary decoding with deep learning models achieved reliable person-dependent classification of user intention, with accuracies ranging from 75% to 97% across participants. These findings identify SPN as an implicit marker for building intention-aware MR interfaces that mitigate the Midas Touch.

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.

Just as people improve decision-making by consulting diverse human advisors, they can now also consult with multiple AI systems. Prior work on group decision-making shows that advice aggregation creates pressure to conform, leading to overreliance. However, the conditions under which multi-AI consultation improves or undermines human decision-making remain unclear. We conducted experiments with three tasks in which participants received advice from panels of AIs. We varied panel size, within-panel consensus, and the human-likeness of presentation. Accuracy improved for small panels relative to a single AI; larger panels yielded no gains. The level of within-panel consensus affected participants' reliance on AI advice: High consensus fostered overreliance; a single dissent reduced pressure to conform; wide disagreement created confusion and undermined appropriate reliance. Human-like presentations increased perceived usefulness and agency in certain tasks, without raising conformity pressure. These findings yield design implications for presenting multi-AI advice that preserve accuracy while mitigating conformity.

In virtual reality, users are typically represented by and interact through a virtual body. Research frequently manipulates different features of these bodies. We analyze 208 studies to identify what aspects of virtual bodies are manipulated, how these manipulations affect interaction and other outcomes, and why they are assumed to do so. Based on the analysis, we propose a design space comprising seven types of visual manipulations: appearance, size, morphology, viewpoint, transfer, remapping, and control. We also synthesize findings on their effects—ranging from task performance to physiological responses and social outcomes—and examine the theories used to explain them, such as embodiment, Proteus effect, and presence. The design space helps researchers identify key variables and their interconnections in design and empirical research of virtual bodies. The synthesis further reveals unexplored causal connections and highlights theories that may account for observed effects.

The way users hold a smartphone depends on the interaction task, yet little is known about the fingers' engagement with the device's surfaces beyond the touchscreen. Such an understanding not only opens up opportunities for novel on- and off-screen interactions, but also the device’s possible physical affordances. We present a study (N=23) that examines the hands' physical engagement with the smartphone beyond the touchscreen across nine mobile interactions. Grasps were annotated from photographs, and contact regions were captured using residual heat traces from grasping the device. Our findings show that fingers and palms adopt a variety of support roles and postures when engaging with the smartphone's back and side edges. The hand-contact maps reveal distinct patterns, differing in contact frequency and placement. This work contributes an empirical characterisation of hands' back and edge engagement, highlighting design opportunities for future smartphone usage extending beyond the touchscreen.

When AI systems allow human-like communication, they elicit increasingly complex relational responses. Knowledge workers face a particular challenge: They approach these systems as tools while interacting with them in ways that resemble human social interaction. To understand the relational contexts that arise when humans engage with anthropomorphic conversational agents, we need to expand existing human-computer interaction frameworks. Through three workshops with qualitative researchers, we found that the fundamental ontological and relational ambiguities inherent in anthropomorphic conversational agents make it difficult for individuals to maintain consistent relational stances toward them. Our findings indicate that people's articulated positioning toward such agents often differs from the relational dynamics that occur during interactions. We propose the concept of relational dissonance to help researchers, designers, and policymakers recognize the resulting tensions in the development, deployment, and governance of anthropomorphic conversational agents and address the need for relational transparency.

While low-cost smartphone-based mobile VR (MVR) improves access to extended reality (XR) technology, it lacks the interaction capabilities of high-end devices. Following PRISMA 2020 methodology, we present a survey of both established and emerging MVR interaction techniques for travel, selection, manipulation, and system control. We reviewed literature from four databases published between 2011–2025 that reported evaluations of MVR interaction techniques. We filtered an initial set of 1041 publications to 64 articles and synthesized the current state of MVR interaction, focusing on cost-accessible approaches. We found many effective low-cost emerging selection and travel techniques, but low-cost object manipulation techniques remain problematic. Acoustic sensing offered superior 3D interaction performance than other sensing modalities while keeping cost low. Our findings inform a novel taxonomy of emerging MVR interaction techniques. We further present a toolkit supporting the design of cost-accessible XR interactions. Our findings underscore practical advantages of DIY approaches to future standalone XR applications developments.

Proliferation of misinformation is a globally acknowledged problem. Cognitive Inoculation helps build resistance to different forms of persuasion, such as misinformation. We investigate Conversational Inoculation, a method to help people build resistance to misinformation through dynamic conversations with a chatbot. We built a Web-based system to implement the method, and conducted a within-subject user experiment to compare it with two traditional inoculation methods. Our results validate Conversational Inoculation as a viable novel method, and show how it was able to enhance participants' resistance to misinformation.A qualitative analysis of the conversations between participants and the chatbot highlighted adaptability, independence, trust and friction as the main factors affecting Conversational Inoculation.We discuss the opportunities and challenges of using Conversational Inoculation to combat misinformation. Our work contributes a timely investigation and a promising research direction in scalable ways to combat misinformation.

Motor-skill learning systems in XR rely on persistent cues. However, constant cueing can induce overreliance and erode memorization and skill transfer. We introduce a skill-adaptive, dynamically transparent ghost instructor whose opacity adapts in real time to learner performance. From a first-person perspective, users observe a ghost hand executing piano fingering with either static or performance-adaptive transparency in a VR piano training. We conducted a within-subjects study (N=30), where learners practiced with traditional Static (fixed-transparency) and our proposed Dynamic (performance-adaptive) modes and were tested without guidance immediately and after a 10-minute retention interval. Relative to Static, the Dynamic mode yielded higher pitch and fingering accuracy and limited error increases. These findings suggest adaptive transparency helps learners internalize fingerings, reducing dependency on external cues and improving short-term skill retention in immersive learning. We discuss design implications for motor-skill learning and outline extensions of this approach to long-term retention and complex tasks.

As modern tabletop play becomes more hybrid through the integration of digital tools, hybrid digital boardgames (HDBs) – games which mix physical and digital components – can be seen as ''gimmicky''. Previous work has explored the use of technology in hybrid play settings, but relatively little work exists on what makes hybridity meaningful in HDBs. In this paper, we present a model for understanding how meaningful hybridity is constructed through the relationship between the technology, game, and player. Over twelve months, we convened a monthly Critical Play Reference Group of 21 local players to play and discuss a curated selection of HDBs. We analysed 37 semi-structured group interviews for qualities of meaningful hybridity across 25 unique published HDBs. This model identifies what players assess in their HDB experience and how that maps to their overall perception of hybridity, informing the design and evaluation of meaningful hybrid game experiences.

Computational tools for fabrication often treat materials as passive rather than active participants in design, abstracting away relationships between craftspeople and materials. For craft communities that value relational practices, abstractions limit the adoption and creative uptake of computational tools which might otherwise be beneficial. To understand how better tool design could support richer relations between individuals, tools, and materials, we interviewed expert woodworkers, fiber artists, and metalworkers. We identify three orders of convivial relations central to craft: immediate relations between individuals, tools, and materials; mid-range relations between communities, platforms, and shared materials; and extended relations between institutions, infrastructures, and ecologies. Our analysis shows how craftspeople engage and struggle with convivial relations across all three orders, creating workflows that learn from materials while supporting autonomy. We conclude with design principles for computational tools and infrastructures to better support material dialogue, collective knowledge, and accountability, along with richer and more convivial relations between craftspeople, tools, and the material worlds around them.

Learning clothes repair is challenging for novices, who face interconnected procedural and embodied challenges, especially when learning alone. Existing tools fail to provide holistic support as interactive tutors and lack awareness of the embodied interactions of working with textiles. This paper presents a multi-phase study that investigates these challenges and explores the design space for a Human-Touch-Aware conversational agent (RepairBot). We began with an in-depth autoethnography to understand the novice experience, which informed the development of the RepairBot Conversation Framework (RBCF) together with a design implementation of a technology probe. Using the RepairBot prototype together with a Wizard-of-Oz approach to simulate Human-Touch-Awareness, we investigated how a conversational agent could support repair learning in novices as well as engage them with their own clothes-repairing projects. Subsequent lab and in-home studies with novice participants suggested specific conversational and embodied mechanisms that would facilitate novices' holistic understanding of repair, increase their confidence, and elicit attentive touch and emotional reflection. We bring these mechanisms together in the framework presented in this paper.

Empathy is widely regarded as inherently positive in supportive online interactions, but its value is shaped by context. This study argues that empathy should be understood not as a uniform good but as a multidimensional, relational practice. Rather than treating empathy as binary, we propose a framework that captures how empathy is solicited in posts and expressed in replies, emphasising that context is critical in determining its appropriateness and effectiveness. Using post–reply data from six Reddit and Stack Exchange communities, we conduct a three-phase study. First, we develop a fine-grained annotation framework to capture distinct empathy practices in both posts and replies. Second, we fine-tune language models to detect these nuanced practices. Third, we apply the models at scale and examine platform- and community-specific patterns of empathy elicitation and expression. Our findings challenge current assumptions about online empathy and offer a more contextualised understanding of its role in online discourse. We identify future directions for platform design and contextual community support.

Creating interactive papercrafts often involves the processes of craft making (e.g., folding, cutting, gluing, etc.) and fabricating the embedded functional circuitry. These two processes are usually separated in the current practice, making the workflow laborious and affecting the in-paper circuit stability. To address the issue of the separated crafting and circuiting processes, we present LiqMetCraft, a toolkit for creating electronics-embedded papercrafts through an integrated process. The toolkit allows users to construct the craft structure by folding and cutting, and forms the circuit traces simultaneously. This is achieved with liquid-metal-dyed paper-like fabric which partially becomes conductive due to the cutting/folding-induced pressure while the unpressed parts of the paper remain insulated. The toolkit consists of software interfaces for papercraft design and hardware components, mainly the liquid-metal-dyed paper-like fabrics and other off-the-shelf components, for physical prototyping. The user studies shows that the participants quickly learned the toolkit and found the integrated process of circuit assembly and shape formation to be engaging and inspiring.

Augmented reality (AR) games hold promise for rehabilitation, yet most remain confined to laboratory studies with limited clinical uptake. Recent advances in spatial computing, especially lightweight, glasses-form-factor AR, create a timely opportunity to embed rehabilitative play into clinical practice and daily contexts. To investigate this potential, we systematically reviewed 132 applications and conducted playtesting with 14 licensed physical therapists. Our analysis revealed three ways therapists re-authored AR games: co-authored play (reshaping movements, progressions, and difficulty), situated play (adapting across specialties, conditions, and contexts), and dual play (mediating both physical recovery and psychological support). We reframe therapists’ frequent phrase—“It depends”—as a generative design principle. This study contributes a clinical reasoning–based framework and design principles and guidelines for creating personalized, situated forms of play that align with therapists’ everyday workflows and inform future lab-to-clinic translation.

Visual perspective is a crucial design factor in Virtual Reality (VR). Especially when complex motor tasks are involved, it can affect both objective performance and subjective experience. We compared four visual perspectives (First-Person view, translucent Ghost view, Third-Person view, and Hybrid view) in a user study (N=20) involving different difficulties in a balancing game. Our findings reveal complex tradeoffs between the sense of embodiment, performance, and preference: The preferred Hybrid perspective offered a significant stability advantage for low task difficulty. However, this benefit vanished with increasing physical demand, revealing a speed-accuracy trade-off where external views required longer completion times. Ego-centric perspectives (First and Ghost) induced a stronger sense of embodiment and presence, but were less preferred. Participants' choice was not determined by representational fidelity but by pragmatic considerations of perceived utility. As perceived effectiveness can overrule objective performance and subjective experience, the choice of perspective is an important factor for future training and rehabilitation applications in VR.

The proliferation of XR devices has made egocentric hand pose estimation a vital task, yet this perspective is inherently challenged by frequent finger occlusions. To address this, we propose a novel approach that leverages the rich information in dorsal hand skin deformation, unlocked by recent advances in dense visual featurizers. We introduce a dual-stream delta encoder that learns pose by contrasting features from a dynamic hand with a baseline relaxed position. Our evaluation demonstrates that, using only cropped dorsal images, our method reduces the Mean Per Joint Angle Error (MPJAE) by 18% in self-occluded scenarios (fingers >= 50% occluded) compared to state-of-the-art techniques that depend on the whole hand's geometry and large model backbones. Consequently, our method not only enhances the reliability of downstream tasks like index finger pinch and tap estimation in occluded scenarios but also unlocks new interaction paradigms, such as detecting isometric force for a surface "click" without visible movement while minimizing model size.

A VR body can move faster than its user, making actions like reaching more efficient. We propose a VR body that not only moves faster during reaching, but also starts moving before the user has decided which target to reach for. However, it is unclear whether such a VR body would speed up choices, since moving towards a wrong target might cause confusion, or influence users' choices. To explore these questions, we built a faster VR body prototype, focusing on an accelerated hand and arm, in a choice task. Thirty-four participants viewed random-dot displays to judge the overall motion direction and indicated their choice by pressing the corresponding button. Task difficulty was varied to influence choice uncertainty. Results showed that choice time decreased when the virtual body was 0.1 seconds ahead of the physical body, but increased when it was 0.3 seconds ahead. Users' choice distributions showed no significant differences.

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.

Ensuring timely takeover in conditionally autonomous vehicles presents a significant challenge, especially when drivers are distracted by non-driving-related tasks or are in suboptimal emotional states. Existing driver monitoring systems struggle with a trade-off between practicality and reliability. Physiological sensors are intrusive, vision-based methods are sensitive to occlusions and variable lighting, and current multimodal learning approaches often rely on simple fusion strategies that fail to reconcile heterogeneous data. We introduce MUST (Multimodal Unified Smartwatch-based Takeover), a framework that predicts driver state and takeover performance using unobtrusive smartwatch signals. MUST employs an asymmetric causal fusion mechanism to model the interplay between driver behavior and emotion. The performance of the architecture was validated in diverse simulator environments reflecting real-world driving conditions, demonstrating robust driver state estimation and takeover prediction. This work establishes the smartwatch as a practical tool for adaptive takeover support, enabling reliable readiness assessment without intrusive hardware or fragile vision systems.

Existing research in steering often focuses on static paths. However, in real-world systems, such as interfaces for lasso and video games, there are no guarantees that the paths will maintain their initial width and distance during steering. We thus explore steering movements on a dynamically varying path, widening or narrowing. To this end, we empirically studied the impact of several task parameters - including changed path width, path occupancy duration, and position - on steering through the dynamically varying path. As a result, we found different steering movements and performance to the previous steering task in the static path in terms of movement time and error rate. Additionally, we tested various previous extended models and found poor fitness results (mean $R^2_{adjusted}=0.53$) compared to the presented models (mean $R^2_{adjusted}=0.92$). We believe our model will assist GUI and game designers in evaluating their applications.

Museums aim at personalizing visits to offer tailored content and encourage visitors to come back. Unfortunately, museum professionals find it difficult to reflect on the vast number of visitor profiles when creating personalized visits. We propose Museo* a new concept to support their creation strategy by allowing the selection of visitor characteristics. Through an interactive design process, we instantiated this concept with MuseoTUI, that displays the progress of visit creation by illuminating physical tokens, and MuseoGUI that displays on a standard touchscreen. In an in-situ comparative structured observation, we evaluated both prototypes. The concept Museo* is well understood and accepted with both interaction styles. MuseoGUI was perceived as more efficient, while MuseoTUI provided better stimulation, higher user experience and the physical manipulation was described as a valuable support for empathy, reflection, and creation. Based on these findings, we present design implications for future systems supporting the creation of personalized visits.

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.

In interpersonal interactions, individuals often exhibit avoidance behaviors toward others they find unpleasant, which can undermine the comfort of everyday social experiences. Existing human-computer interaction (HCI) research has primarily focused on promoting social connections, while support for avoidance-oriented social situations remains underexplored. To address this gap, we propose leveraging Diminished Reality (DR) technology to obscure perceptual cues of undesirable individuals. We designed and implemented a mixed reality prototype system and conducted experiments manipulating both the occlusion method and social distance. Results indicate that DR significantly reduces users' social anxiety and sense of social presence. Moreover, participants generally expressed positive attitudes toward usage intention and ethical considerations. This work extends HCI research on social comfort, shifting the focus from "facilitating connection" to "supporting avoidance".

Generative Artificial Intelligence (GAI) offers new opportunities for reconstructing these unrecorded memory scenes, yet existing web-based tools undermine users' sense of agency through disengaging and unpredictable interactions. In this work, we advance three design arguments about how slow, tangible interaction can reshape human–AI relationships by making temporality, embodied agency, and generative processes experientially legible. We instantiate these arguments by presenting Memory Printer, a tangible design exemplar that combines silk-screen printing metaphors with text-to-image generation. The design features layered reconstruction that decomposes image generation into incremental steps, a physical wooden scraper enabling embodied control over image revelation, and built-in printing that produces tangible photos. We examine these arguments through a comparative study with 24 participants, exploring how participants engage with, interpret, and respond to this interaction stance. The study surfaces both opportunities—such as vivid memory evocation, heightened sense of control, and creative exploration—and critical tensions, including risks of false memory formation, algorithmic bias, and data privacy. Together, these findings articulate important boundaries for deploying generative AI in emotionally sensitive contexts.

Current co-op games keep collaboration virtual even when players are physically co-located in the same room, limiting embodied coordination in the shared space. We introduce MoveTogether, a novel physical co-op gameplay in which two players jointly operate a single, tracked prop, adding a shared physical communication channel on top of visual and audio cues. To explore the design space in mixed reality, we conducted a workshop with 10 professional designers, generating a physical co-op design space that encompasses prop and interaction design patterns, and how they relate to affordance and cooperative experience. In a within-subjects study of virtual vs. physical co-op experiences (n=16), we observed finer-grained task coordination, fewer collisions, and more strategy-focused communication. Players reported higher collaboration, sense of achievement, enjoyment, and overall preference for physical co-op. This work opens a new design space for co-located play and offers guidance for designing embodied co-op experiences.

Conceptual CAD requires transforming functional requirements into parametric 3D models, yet existing systems have steep learning curves and limit creativity through premature fixation. Generative AI shows promise in producing diverse alternatives, while current methods mainly reconstruct CAD modeling sequences of existing designs, making them unsuitable for early stages where ideas are vague and intent is difficult to express. We present Req2CAD, an interactive system that enables designers to progress from design problems toward conceptual CAD models through functional decomposition, function–structure reasoning, and component-level CAD creation and iteration. Req2CAD introduces a data annotation pipeline that maps functional requirements to the 3D structural design space, a dual-feature CAD representation to support design space exploration and CAD ideation, and a progressive CAD generation method that enables rapid CAD model creation through multi-modal intent expression. A technical evaluation and user study demonstrate the effectiveness of Req2CAD, highlighting its potential for human–AI co-creation.

Traditional pianos are inherently non-portable, restricting everyday accessibility and on-demand creativity. Existing portable alternatives, largely vision-based with external cameras, suffer from limited range, occlusion, and unreliable contact detection. We present PianoBand, a wrist-worn system integrating an IMU, a miniature under-wrist RGB camera, and a printed keyboard sheet augmented with fiducial markers for reliable key mapping on any flat surface. Powered by a lightweight real-time IMU–vision pipeline, PianoBand enables high-fidelity piano interaction, supporting single notes, multi-finger chords, flexible fingering, dynamic velocity, and preliminary articulation techniques. Technical evaluation showed robust tap detection (over 99% accuracy) and accurate fingertip localization (8.90 pixels error), enabling precise note mapping. A comparative user study (N=15) further evaluated system performance, reporting high note accuracy, comparable to roll-up pianos and outperforming an XR piano, along with high ratings for portability, expressivity, and extensibility. Expert interviews highlighted broad application opportunities for piano-based experience and music creation, suggesting future design directions.