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.

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.

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.

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.

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.

In what ways do generative AI (GenAI) tools embedded in mainstream design software affect UI design practices and outcomes? In this study, we examine the use of FigmaAI, a GenAI feature within the industry-standard platform Figma. We conducted a within-subject study with 16 professional UX designers, each of whom completed two high-fidelity UI design tasks in a think-aloud session: one conventionally, without AI, and one with FigmaAI. We analyse the design process itself alongside experiences and reflections on using and not using AI, gathered from adjacent semi-structured interviews and post-task questionnaires. Our findings suggest that GenAI reshapes UI workflows, shifting them from additive to subtractive processes: designers refine AI drafts rather than building interfaces from scratch. While AI reduces workload and accelerates initial setup, it also constrains exploration, limits perceived ownership, and produces designs that are more visually and structurally similar.

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.

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.

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.

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.

Existing research has examined how artificial teammates influence collaboration within teams, but far less is known about their role in shaping interactions between teams. In particular, it remains unclear how transparent integration of AI teammates influences intergroup biases in competitive contexts. To investigate this, we designed StarHarvest, an online game where two hybrid teams (each consisting of one human and one bot, either concealed or revealed) competed for resources while bots elicited prosocial or antisocial behaviors. Drawing on data from 240 participants, we analyzed behavioral choices, evaluations, and resource allocations toward ingroup and outgroup members. Our findings show that hidden bots fostered stronger within-team coordination but also allowed asymmetric retribution toward weaker opponents. By contrast, revealed bots were treated as secondary teammates, reducing cohesion and shifting responsibility onto human partners. We conclude with design implications for socially responsible integration of artificial teammates, highlighting tensions between group-level and agent-level identities.

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.

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.

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.

LLMs are now embedded in a wide range of everyday scenarios. However, their inherent hallucinations risk hiding misinformation in fluent responses, raising concerns about overreliance on AI. Detecting overreliance is challenging, as it often arises in complex, dynamic contexts and cannot be easily captured by post-hoc task outcomes. In this work, we aim to investigate how users' behavioral patterns correlate with overreliance. We collected interaction logs from 77 participants working with an LLM injected plausible misinformation across three real-world tasks and we assessed overreliance by whether participants detected and corrected these errors. By semantically encoding and clustering segments of user interactions, we identified five behavioral patterns linked to overreliance: users with low overreliance show careful task comprehension and fine-grained navigation; users with high overreliance show frequent copy-paste, skipping initial comprehension, repeated LLM references, coarse locating, and accepting misinformation despite hesitation. We discuss design implications for mitigation.

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.

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.

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.

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.

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.

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.

Effortless manipulation informs and relies on preshaping: the subconscious posing of the hand before grasping. Virtual environments and the design of interaction techniques alters interaction requirements like contact and reach, forcing behavioural adaptation. We present a comparative study investigating preshaping behaviour across direct versus indirect (gaze-assisted) and bare-hand versus controller techniques on a docking task. Results reveal that response patterns scale with anticipated task difficulty, and that direct techniques elicit effective posing of the hand. Indirect techniques shortcut hand transport and, in turn lacks the sensory feedback to guide planning, inducing efficient but attenuated responses that necessitate compensatory manipulation and clutching. Notably, controllers that afford in-hand rotation allow users to extend their range of motion. These findings can inform interaction design to better afford preshaping and optimise 3D manipulation tasks.

Large Language Model-powered conversational agents (CAs) are increasingly capable of projecting sophisticated personalities through language, but how these projections affect users is unclear. We thus examine how CA personalities expressed linguistically affect user decisions and perceptions in the context of charitable giving. In a crowdsourced study, 360 participants interacted with one of eight CAs, each projecting a personality composed of three linguistic aspects: attitude (optimistic/pessimistic), authority (authoritative/submissive), and reasoning (emotional/rational). While the CA's composite personality did not affect participants' decisions, it did affect their perceptions and emotional responses. Particularly, participants interacting with pessimistic CAs felt lower emotional state and lower affinity towards the cause, perceived the CA as less trustworthy and less competent, and yet tended to donate more toward the charity. Perceptions of trust, competence, and situational empathy significantly predicted donation decisions. Our findings emphasize the risks CAs pose as instruments of manipulation, subtly influencing user perceptions and decisions.

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.

While autonomous vehicles (AVs) continue to advance and reshape modern transportation, they remain unable to navigate all traffic conditions without human input, highlighting the need for remote human intervention in edge-case scenarios. Two major teleoperation paradigms have emerged to address this need: tele-driving and tele-assistance. In tele-driving, remote operators (ROs) continuously control the AV through direct access to its actuators. In tele-assistance, ROs provide high-level instructions through a specialized interface, with low-level maneuvers delegated to the AV. We conducted a quantitative comparison of these paradigms, examining four edge-case scenarios: one uses a steering wheel and pedals, the other employs discrete high-level commands through a Wizard-of-Oz methodology. We measured mental workload, situation awareness, time completion, and overall user experience (UX). Results indicate that the tele-assistance interface reduced operators’ mental workload and improved situation awareness, suggesting the need for further development of tele-assistance interfaces.

Human–AI co-creativity is often understood through a tool-use or collaboration frame, obscuring the relational dynamics of artistic practice with machine learning (ML) systems. To advance the field, we recast such artistic practice through Material Engagement Theory (MET), emphasizing how creative and aesthetic processes emerge in sustained relations between artist and system. We examined 18 contemporary artists’ engagements with ML from 54 documents using a qualitative, interpretive, and framework-guided approach. Our findings show how artists and ML systems co-constitute creative and aesthetic properties by mutually discovering and attuning to each other’s affordances, where creativity unfolds along a control-chance continuum driven by creative and aesthetic thinging, enabling a mutual aesthetic becoming through sustained interaction. Key factors include developing artistic intuition for ML, internalisation, and the evolving role of the meta-artist. Herewith, we contribute MET as a framework for enriching our understanding of human–AI co-creativity as emergent and relational.

In crowdsourced user experiments that collect performance data from graphical user interface (GUI) interactions, some participants ignore instructions or act carelessly, threatening the validity of performance models. We investigate a pre-task screening method that requires simple GUI operations analogous to the main task and uses the resulting error as a continuous quality signal. Our pre-task is a brief image-resizing task in which workers match an on-screen card to a physical card; workers whose resizing error exceeds a threshold are excluded from the main experiment. The main task is a standardized pointing experiment with well-established models of movement time and error rate. Across mouse- and smartphone-based crowdsourced experiments, we show that reducing the proportion of workers exhibiting unexpected behavior and tightening the pre-task threshold systematically improve the goodness of fit and predictive accuracy of GUI performance models, demonstrating that brief pre-task screening can enhance data quality.

As generative AI tools become embedded in creative practice, questions of ownership in co-creative contexts are pressing. Yet studies of human-AI collaboration often invoke "ownership" without definition: sometimes conflating it with other concepts, and other times leaving interpretation to participants. This inconsistency makes findings difficult to compare across or even within studies. We introduce a framework of creative ownership comprising three dimensions - Person, Process, and System - each with three subdimensions, offering a shared language for both system design and HCI research. In semi-structured interviews with 21 creative professionals, we found that participants’ initial references to ownership (e.g., embodiment, control, concept) were fully encompassed by the framework, demonstrating its coverage. Once introduced, however, they also articulated and prioritized the remaining subdimensions, underscoring how the framework expands reflection and enables richer insights. Our contributions include 1) the framework, 2) a web-based visualization tool, and 3) empirical findings on its utility.

AI VTubers, where the performer is not human but algorithmically generated, introduce a new context for fandom. While human VTubers have been substantially studied for their cultural appeal, parasocial dynamics, and community economies, little is known about how audiences engage with their AI counterparts. To address this gap, we present a qualitative study of Neuro-sama, the most prominent AI VTuber. Our findings show that engagement is anchored in active co-creation: audiences are drawn by the AI's unpredictable yet entertaining interactions, cement loyalty through collective emotional events that trigger anthropomorphic projection, and sustain attachment via the AI's consistent persona. Financial support emerges not as a reward for performance but as a participatory mechanism for shaping livestream content, establishing a resilient fan economy built on ongoing interaction. These dynamics reveal how AI Vtuber fandom reshapes fan–creator relationships and offer implications for designing transparent and sustainable AI-mediated communities.

Embodying natural entities in Virtual Reality (VR) shows potential to enhance nature connectedness, but design factors that support such embodiment remain underexplored. This study examined whether transitional elements in the physical setting before and after VR and multisensory stimuli during VR can strengthen nature connectedness in a transformative tree-embodiment experience. Through a mixed-methods approach (N=20), where we varied the pre- and post-VR experience (Neutral vs. Transitional) and sensory modalities (Audiovisual vs. Multisensory), we found that both transitional and multisensory experiences significantly enhanced presence, embodiment, and nature connectedness, with increases in emotional connectedness sustained one week later. Drawing on interview insights and impact ratings of specific design features, we derive design recommendations for integrating transitional and multisensory elements. Our findings demonstrate the value of holistic design for enhancing the emotional and transformative potential of VR nature embodiment for fostering environmental awareness.

Creative tasks require creators to iteratively produce, select, and discard potentially useful ideas. Now, creativity tools include generative AI features (e.g., Photoshop Generative Fill) that increase the number of alternatives creators consider through rapid experiments with prompts and random generations. Creators use tedious manual systems for organizing their prior ideas by saving file versions or hiding layers, but they lack the support they want for reusing prior alternatives in personal work or in communication with others. We present HistoryPalette, a system that supports exploration and reuse of prior designs in generative image creation and editing. Using HistoryPalette, creators and their collaborators explore a "palette" of prior design alternatives organized by spatial position, topic category, and creation time. HistoryPalette enables creators to quickly preview and reuse their prior work. In creative professional and client collaborator user studies, participants generated and edited images by exploring and reusing past design alternatives with HistoryPalette.

Teaching assistants (TAs) play a critical role in computing and HCI education, yet little is known about how they perceive and use AI tools or imagine their future pedagogical uses. We report on a series of design workshops with 131 computing (CS) TAs across two U.S. universities. These workshops invited TAs to reflect on current AI use and envision future AI-enhanced tools and practices. Drawing on surveys and design artifacts, we (1) develop a cross-institutional typology of situated TA uses of AI, revealing opportunities and tensions; (2) show how TAs’ visions of AI are shaped by disciplinary norms, institutional structures, and their intermediary position as student-instructors; and (3) reveal ethical dilemmas. Our findings contribute to HCI by positioning TAs as AI-supported knowledge workers in the education domain; illustrating how design and speculation are shaped by people’s situated understandings of AI and their institutional contexts; and identifying a core tension in which TAs simultaneously preserve and erode the human dimensions of their work, with implications for future instructional tools and human–AI collaboration.

This paper reconsiders knowledge sharing as a relational process of disorientation and reorientation, which is a way of turning toward others, the world, and possible futures. Drawing on an intergenerational participatory speculative design project in a historically Black neighborhood, we show how seniors and youth shared knowledge of turning toward the affective, more-than-human relations, as well as toward one another and collective futures. These practices reoriented participants across differences toward one another and their community, cultivating new cross-generational relationships and shared imagination. Building on Sara Ahmed's notion of orientation and Black feminist thought, we argue that knowledge sharing is less about efficiency or productivity and more about relational alignment---negotiating how communities come together and move together toward otherwise futures. For HCI, this critical reframing foregrounds the racialized histories and everyday labors that sustain collective orientations, urging scholars and designers to consider how communities can collectively (re)orient themselves epistemically and ontologically through design, and what otherwise worlds those reorientations make possible.

Scrolling is ubiquitous in our daily computing experience. We explore how single-handed microgestures can be used for scrolling. Based on an analysis of the basic components necessary for scrolling, we selected 3 microgestures: Tap, Hold and Drag. Considering both rate and position controls, we designed 4 microgesture-based scrolling techniques adapted to these 3 microgestures. We contrasted these 4 techniques in a laboratory experiment with 24 participants who performed 2 tasks: a reciprocal selection task, where participants scrolled the view to reach and select a target; and a counting task, where participants scrolled the view to count image occurrences. Our results suggest that the technique based on Drag microgestures with rate control is the most effective for scrolling operations, regardless of the task. This work demonstrates that microgestures, with their advantages for frequent everyday tasks, offer a promising approach to continuous and efficient scrolling control.

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.

Pet loss is a distressing experience often underappreciated by societal norms, leading to disenfranchised grief. We investigate how bereaved pet owners engage in online support groups, focusing on their motivations, interactions, and challenges. Through in-depth interviews with 18 participants, we identified key motivations for joining, including grief expression and validation, emotional and informational support, anonymity and accessibility. Engagement in these groups facilitated emotional expression, grief validation, memorialization practices, and the development of coping mechanisms, while also fostering shared rituals and collective identity. However, challenges like compulsory grief—where grievers feel pressured to remain in a constant state of mourning—and insufficient support for dynamic coping persisted. Drawing on the dual process model of bereavement, we propose the metaphor of oscillation design, balancing loss-oriented and restoration-oriented coping. Our findings show that current platforms overemphasize loss, underscoring the need for design interventions that rebalance asymmetric oscillation and enable more dynamic coping trajectories.

Current Extended Reality (XR) devices are increasingly being used as productivity tools. Compared to conventional setups, they allow for more flexibility in dynamic work locations beyond the desktop while providing a large virtual workspace. Recent research has explored how users organize digital documents and how virtual interfaces could be adapted to different locations and scenarios. However, there has been limited research on how location changes affect productivity tasks in XR environments and how users manually adapt virtual content layouts after such task interruptions. To address this, we conducted an exploratory user study (N=17) in which participants worked on a document-centered organization and planning task while changing locations every five minutes. We examined how these spatial transitions interfered with the task and identified layout strategies and patterns. From our observations and participant responses, we derived a set of design guidelines to inform the development of future XR knowledge work systems in mobile contexts.

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.

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.

Everyday object-based interactions (EOIs) and mid-air gesture interactions (MAIs) have been widely explored, yet prior work on their integration often targets narrow use cases or specific technologies, leaving designers and developers with limited guidance that generalizes across diverse EOIs and MAIs. We introduce Objestures (“Obj” + “Gestures”)—five interaction types spanning EOIs and MAIs, forming a design space for expressive uni- and bimanual interaction. To evaluate the usefulness of Objestures, we conducted an exploratory user study (N=12) on basic 3D tasks (rotation and scaling), which showed performance comparable to the headset's native freehand manipulation. To understand the user experience, we conducted case studies with the same participants across three applications (Sound, Draw, and Shadow), where participants found the interactions intuitive, engaging, and expressive, and indicated interest in everyday use. We further demonstrate the potential of Objestures across diverse contexts through 30 examples, and discuss limitations and implications.

Social video platforms such as YouTube and Twitch increasingly moderate noncompliant video content, yet we know little about what psychological factors drive creators to produce such videos. Drawing on theories of self-control and moral disengagement, we examine how self-control and moral disengagement influence creators' production of noncompliant videos, their moderation experience, and, once moderated, their perceived fairness of moderation decisions and their coping strategies. By analyzing data from a survey with 400 video creators, we find that moral disengagement increases the creation of noncompliant videos and moderation experience, while self-control reduces them. Self-control and moral disengagement influence creators’ adoption of coping strategies in response to moderation decisions, but in distinct ways. The effects of moral disengagement and self-control are moderated by creators' reliance on video creation for income. These findings offer a fuller account of why creators offend. We discuss implications for better supporting punished creators’ behavioral improvement.

With the growing prevalence of online mis/disinformation encountered by children, digital media literacy has become an urgent concern. Existing research emphasizes cognitive models, focusing on individual reasoning and specific quantitative criteria to classify people’s information literacy. However, critics argue that focusing solely on cognitive approach neglects the social, emotional, and cultural contexts that shape how mis/disinformation is created and spread. In this study, we expand beyond the cognitive model by examining socioemotional learning (SEL) and sociocultural (SC) perspectives. To explore how children conceptualize mis/disinformation through these lenses, we conducted 26 co-design workshops with children ages 6–11 over a 2.5-year period. Our findings highlight children’s awareness of emotional responses, peer pressure, financial incentives, and the importance of community support. These insights contribute to HCI by foregrounding the need for design approaches that integrate cognitive, SEL, and SC dimensions. We present an integrated framework to inform how community groups can support children and design recommendations that address the growing sophistication of mis/disinformation.

While Virtual Reality (VR) is increasingly employed for stress management, most applications rely heavily on audio-visual stimuli and overlook the therapeutic potential of squeezing engagement. To address this gap, we introduce VR Calm Plus, a multimodal system that integrates a pressure-sensitive plush toy into an interactive VR environment. This interface allows users to dynamically modulate the virtual atmosphere through physical squeezing actions, fostering a deeper sense of embodied relaxation. We evaluated the system with 40 participants using PANAS-X surveys, subjective questionnaires, physiological measures (heart rate, skin conductance, pulse rate variability), and semi-structured interviews. Results demonstrate that, compared to a visual-only baseline, squeeze-based interaction significantly enhances positive affect and perceived relaxation. Physiological data further revealed a state of “active relaxation”, characterized by greater reductions in heart rate and preserved autonomic flexibility (PRV), alongside sustained emotional engagement (GSR). Our findings highlight the value of coupling tangible input with immersive environments to support emotional well-being and offer design insights for future VR-based mental health tools.

Generative AI is increasingly present in children’s learning environments, yet little is known about how families navigate this technology in middle childhood (ages 7–13), when parental guidance remains strong but children seek independence. \rev{Drawing on self-directed learning (SDL), we explore how parents in our exploratory sample perceived children’s emerging self-directness and agency.} Through focus groups with 13 parent–child pairs, we examine parents’ views on children’s AI literacy development, readiness factors, and mediation strategies. Parents described emergent pathways shaped by screen time, self-directness, and knowledge growth. They often confined AI to learning-only contexts, positioning it as a tutor while overlooking non-learning uses and risks such as privacy and infrastructural embedding. Many acknowledged limited AI literacy and turned to joint engagement as opportunities for co-learning. Our findings surface possible parental pathways of children’s AI literacy, highlight gaps between pragmatic expectations and critical literacies, and offer situated design considerations for AI systems that scaffold SDL while balancing oversight with autonomy.

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.

How might alternative encounters with personal hiking data support practices of noticing nature as well as changes in one’s self over time? To investigate this question, we conducted a multi-year first person study with Capra—a system that combines the collection and exploration of hiking experiences in nature with an emphasis on longer-term, occasional yet indefinite use. Over several years, three researchers that represented different hiking frequencies, paces, locations, and life stages concurrently and independently hiked, used, and lived with Capra. Findings revealed unique individual and collective changes in attitude among the team, from an initial interest in intentionally capturing specific natural phenomena towards a shift in attentiveness when re-exploring hikes as well as when hiking outdoors. It is these insights that emerged through our long-term experiences with Capra that we present and reflect on in this paper.

We propose a method to fabricate objects composed of 3D printed flattened pieces with integrated zipper-like structures. The object is manually assembled into a 3D shape by connecting the zipper components. By employing a zipper design that allows for angle-independent connections between patches, our method enables both the surface and zipper components to be printed in the same orientation, resulting in high-quality reconstruction of the input model with a faster 3D printing process that wastes less material. We implement a fully automated pipeline that takes a 3D model as input, converts it into developable patches, generates the zipper structures, and flattens them for subsequent 3D printing. We demonstrate that our approach significantly reduces the fabrication time and support material consumption. We also present application examples that highlight the versatility of our method.