As Extended Reality (XR) transitions from specialized domains into domestic settings, industry narratives envision a future of seamless, ubiquitous integration. Yet these imaginaries, largely shaped by Western contexts, often overlook the complex social organization and material constraints of diverse households. To address this gap, we examined how individuals in Singapore interpret XR in everyday life. Using value scenarios as sociotechnical imaginaries, we conducted a survey (N = 206) and interviews (N = 22). We identify two layers of mental models: (1) perceived immersion and (2) XR’s roles in domestic life. Through these models, participants conceptualized XR as a situational fix for overcoming spatial, temporal, or relational constraints, or as an enabling medium for connection, expression, and wellbeing. We argue for a shift from functional optimization to relational maintenance, and propose design considerations for XR as an episodic, situational utility that supports the home.

Eating disorder (ED) is a psychiatric condition that involves behaviors like binge and restrictive eating with severe health consequences, particularly prevalent among young women. While technology interventions exist, they typically focus on retrospective reflection or general management, missing the time window when an ED behavior is taking place. In this work, we conducted co-design sessions with 22 young women experiencing EDs to develop ideas for Just-in-Time (JIT) interventions, followed by interviews with five experts specialized in ED treatment. We found that eating plays varied roles in participants’ lives—from a means of gaining autonomy to automatic physiological responses—leading to design ideas including behavioral warnings, appetite management, food option redirection, psychological support systems, etc. By examining the characteristics of these designs with expert perspectives, we discuss what JIT support means for ED care and how to make it effective and sustainable. © 2026 Copyright held by the owner/author(s).

While previous research has attempted to link features of individuals’ drawings to their emotional states, it often overlooks the deeply personal and context-driven nature of visual expression. To bridge the gap, we conducted a two‑week diary study with 21 participants, who used a custom‑built app to track daily emotions through free drawings, followed by interviews reflecting on their artwork. Among the 252 drawings gathered, we found no strong correlations between reported emotions and measurable drawing behaviors; instead, participants expressed emotions through diverse approaches, from illustrations of emotion sources (e.g., events, objects) and metaphors, to emojis, literal text and spontaneous, random mark-making. Participants developed consistent personal styles and described drawing as an intuitive, playful, and safe outlet, though some faced challenges with the ambiguity of visual expressions and interpreting their creations afterwards. With the lessons learned, we discuss opportunities for designing expression-centered emotion tracking technologies that embrace individuality and creativity.

Gaming is a meaningful part of children’s lives, yet its safety has drawn increasing concerns from scholars and the public. On platforms like Roblox, children may encounter extremist roleplay, scams, or virtual rape. Prior research has emphasized technical interventions that address risks after they occur and ethical frameworks for game design, but children’s perspectives on safety design remain missing. To address this gap, we conducted a cooperative inquiry study to co-design safety mechanisms with 22 children aged 7–12. Children proposed designs emphasizing transparent information about games and purchases, community accountability through reporting and reviews, player empowerment to manage social boundaries and engagement, and age-appropriate game navigation. Our findings extend safety-by-design research by foregrounding children’s perspectives, showing how they envision safety mechanisms across both game and platform design, while enjoying safe play through risk exposure, allocating trust, and balancing platform support with agency.

For university students transitioning to an independent and flexible lifestyle, having ADHD poses multiple challenges to their academic task management, which are closely tied to their metacognitive struggles—difficulties in awareness and regulation of one’s own thinking processes. The recently surged Generative AI shows promise to mitigate these gaps with its advanced information understanding and generation capabilities. As an exploratory step, we conducted co-design sessions with 20 university students diagnosed with ADHD, followed by interviews with five experts specialized in ADHD intervention. Adopting a metacognitive lens, we examined participants’ ideas on GenAI-based task management support and experts’ assessments, which led to three design directions: providing cognitive scaffolding to enhance task and self-awareness, promoting reflective task execution for building metacognitive abilities, and facilitating emotional regulation to sustain task engagement. Drawing on these findings, we discuss opportunities for GenAI to support the metacognitive needs of neurodivergent populations, offering future directions for both research and practice.

Large language model (LLM) based AI applications are being rapidly adopted by various creativity-related sectors, including UX design. However, as newly emerged applications, how UX designers work with LLMs and how to optimize the benefits of LLMs in UX design remain unclear. Leveraging the widely adopted LLM application ChatGPT as a case study, we recruited 12 experienced frontline UX practitioners from IT companies to use ChatGPT in their everyday design activities for 4 to 6 weeks. Through use logs, questionnaires, and interviews, we collected participants’ usage and reflection data. Our analysis reveals the different functions of ChatGPT in facilitating UX design, such as offering design guidelines, constructing user profiles, and simulating stakeholders. Challenges also emerged, such as limitations in understanding complex design problems and prototyping design ideas. Based on the findings, we reflect on the working dynamics between human workers and AI tools and suggest implications for designing more usable LLM-based AI applications.

AI-powered technologies are becoming increasingly integral to children’s digital experiences through devices like interactive toys, home automation systems, and apps, offering rich, personalized, and dynamic interactions. Despite their growing prevalence, how these AI-powered platforms can be designed to address the unique needs of children remains largely underexplored. Leveraging family interactions with Smart Voice Assistants (VAs) as a case study, we aim to explore how to approach child-centered AI (CCAI) design from a family perspective in this work. Specifically, we interviewed 20 parents and observed children’s VA interactions in eight households in a non-Western context. Using the theoretical lenses of agency and family functioning, we provide empirical insights into family dynamics when interacting with VAs in a less studied cultural setting, such as variations in family interaction types around VAs, the autonomy exercised by different parties, and the family functional roles VAs played. Based on these findings, we argue that CCAI design should be understood as balancing children’s agency, the roles and goals of other involved actors, and the contexts in which AI is used, and that it should focus on creating AI technologies that support positive outcomes for children in ethical ways while thoughtfully considering other stakeholders and their varying purposes for engaging with AI. In doing so, we offer a reconceptualization of CCAI and point to design directions for AI technologies that more meaningfully center child users in family contexts.

Grandparents play a central role in co-parenting in many Asian households, particularly when both parents work full-time.While this intergenerational caregiving arrangement offers emotional and practical benefits, it also introduces communication challenges rooted in generational differences in parenting values and expectations.Therefore, we explore how grandparents and parents in Hong Kong navigate communication around young children's upbringing, and how technology mediates these interactions.Based on semi-structured interviews with ten preliminary participants (five grandparents and five parents), our early findings reveal key areas of communication and conflict, especially around educational decisions and caregiving responsibilities.Participants also shared the use of digital tools, such as messaging apps, in facilitating coparenting communication.This work highlights the need for more inclusive, elderly-friendly technological interventions and offers early design considerations for tools that support clearer, more empathetic intergenerational dialogue in child caregiving contexts.These insights contribute to ongoing efforts to design culturally sensitive technologies for multigenerational families.

The Illusion of Sunset" (Nature Science) Content preview that re-organizes the text into Cornell-style Notes based on the reader's prior knowledge and reading habits (P1)."Quantum Entanglement" (Physics) Background music that simulates the sounds in an atomic world, while blocking external noise to help the reader stay focused (P7)."The Illusion of Sunset" (Nature Science) An "attention flow" panel highlighting the reader's current focused text area while fading other text, powered by an eye-tracking system (P6)."Bamboo Creek" (Ancient Chinese Literary) Tactile, sound, and olfactory stimuli that enable the reader to feel, hear, and smell the bamboo forest described in the article (P7)."Category Theory" (Mathematics) Bright, colourful visual decorations (e.g., small flowers) that make the reading material appealing, and thus sustain the reader's motivation (P10)."Quantum Entanglement" (Physics) A background simulating internet virus with intense colors, urging the readers to finish reading as soon as possible (P4)

User-generated game (UGG) platforms such as Roblox have become increasingly popular among children but are also criticized for hosting rampant online risks, such as virtual gang rape and spread of extremist ideologies. However, limited research has explored the risks from child players’ perspectives. Through an interview study with 26 child players, we found three categories of risks: varied scams, the normalization of anti-social behaviors, and adult roleplays. We also identified three types of safety practices child players employed on UGG platforms: adaptive safety practices across different social relationships, applying heuristics to safeguard their safety, and tinkering with safety features. We discuss design-mediated risks in UGGs targeting vulnerable child players and challenges and opportunities for risk mitigation strategies in UGGs. Lastly, we provide design implications for UGG platforms to support child players and provide a safe place for them to play.

2025 CHI conference on Human Factors in Computing Systems, Yokohama, Japan, 26 April - 1 May 2025

Waiting for system loading is a common scenario that often diminishes user experience, leading to dissatisfaction. Well-established visual indicators like progress bars can not directly apply to the interactions with voice assistants (VAs) like Siri. As VAs continue to rise in popularity, this research aims to explore the design of auditory indicators, particularly human speech, for optimizing waiting experiences in Voice User Interfaces (VUIs). We first organized focus groups (N=35) to identify design considerations for speech indicators, uncovering design opportunities in integrating explanations and humor. Subsequently, we conducted an empirical study (N=30) to evaluate the effects of speech indicators with two levels of explanation and humor on the waiting experience, measured by attention, perceived time, pleasure, and overall satisfaction, during both short and long loading durations. Our findings suggest significant potential for incorporating explanations and humor into VUIs, offering actionable insights for designing effective speech indicators that improve waiting experiences.

2025 CHI conference on Human Factors in Computing Systems, Yokohama, Japan, 26 April - 1 May 2025

Advances in artificial intelligence have led to breakthroughs in large language models (LLMs), like ChatGPT, opening up exciting possibilities for conceptual design. However, it’s essential to gain an in-depth understanding of how LLMs impact conceptual design output, process, and human designers’ perception. To this end, we chose ChatGPT as an example and conducted the investigation with 30 participants divided into Human-LLMs groups and human-human groups. The results indicated that there was no significant difference between their outputs, but the incorporation of LLMs shortened the completion time with fewer design steps and less time allocated to the late stages of design. Despite being perceived as less efficient and trusted, LLMs can still be viewed as potential collaborators, with humans holding the leadership. These findings offer the HCI community a thorough comprehension of how LLMs influence creativity-related practices, providing valuable insights for designing future interactions with LLMs.

The rapid development of spatial transcriptomics (ST) has revolutionized the study of spatial heterogeneity and increased the demand for comprehensive methods to effectively characterize spatial domains. As a prerequisite for ST data analysis, spatial domain characterization is a critical step for downstream analysis and biological interpretation. Here, we propose a deep graph contrastive learning framework (spG-CLF) for spatial transcriptomics, which leverages contrastive learning through graph convolutional networks to effectively learn features among spots, addressing the issue of poor cross-platform generalizability. By alternately performing attribute and topological denoising, our method specifically reduces noise in ST data. We demonstrate that s p GCLF is effective for spatial domain identification, trajectory inference, multi-slice integration, and type annotation.

With the rise of remote and hybrid work after COVID-19, there is growing interest in understanding remote workers’ experiences and designing digital technology for the future of work within the field of HCI. To gain a holistic understanding of how remote workers navigate the blurred boundary between work and home and how designers can better support their boundary work, we employ humanistic geography as a lens. We engaged in co-speculative design practices with 11 remote workers in the US, exploring how future technologies might sustainably enhance participants’ work and home lives in remote/hybrid arrangements. We present the imagined technologies that resulted from this process, which both reinforce remote workers’ existing boundary work practices through everyday routines/rituals and reclaim the notion of home by fostering independence, joy, and healthy relationships. Our discussions with participants inform implications for designing digital technologies that promote sustainability in the future remote/hybrid work landscape.

Hand gestures are widely used in daily life for expressing emotions, yet gesture input is not part of existing emotion tracking systems. To seek a practical and effortless way of using gestures to inform emotions, we explore the relationships between gestural features and commonly experienced emotions by focusing on single-hand gestures that are easy to perform and capture. First, we collected 756 gestures (in photo and video pairs) from 63 participants who expressed different emotions in a survey, and then interviewed 11 of them to understand their gesture-forming rationales. We found that the valence and arousal level of the expressed emotions significantly correlated with participants’ finger-pointing direction and their gesture strength, and synthesized four channels through which participants externalized their expressions with gestures. Reflecting on the findings, we discuss how emotions can be characterized and contextualized with gestural cues and implications for designing multimodal emotion tracking systems and beyond.

Parents play essential roles in children’s play and learning with various media, often leading to positive and productive engagement outcomes for both parties. As such, an increasing number of HCI research has focused on understanding parent-child joint media engagement (JME) and designing new technologies to foster productive joint media experiences for children and parents. However, we currently lack a systematic view of this emerging field, which hinders the research and design of new joint media experiences and technologies for families. In this work, we conduct a scoping review of parent-child JME research within HCI (N = 89) and analyze the included papers from three lenses: publication features, methodological features, and JME features. Based on these findings, we identify gaps and opportunities in parent-child JME research and further expand the theoretical framing of JME by developing a framework that captures different JME dimensions.

Benefiting many information retrieval applications, named entity recognition (NER) has shown impressive progress. Recently, there has been a growing trend to decompose complex NER tasks into two subtasks (e.g., entity span detection (ESD) and entity type classification (ETC), to achieve better performance. Despite the remarkable success, from the perspective of representation, existing methods do not explicitly distinguish non-entities and entities, which may lead to ESD errors. Meanwhile, they do not explicitly distinguish entities with different entity types, which may lead to entity type misclassification. As such, the limited representation abilities may challenge some competitive NER methods, leading to unsatisfactory performance, especially in the low-resource setting (e.g., cross-domain NER). In light of these challenges, we propose to utilize contrastive learning to refine the original chaotic representations and learn the generalized representations for cross-domain NER. In particular, this article proposes a dual contrastive learning model (Dual-CL), which respectively utilizes a token-level contrastive learning module and a sentence-level contrastive learning module to enhance ESD, ETC for cross-domain NER. Empirical results on 10 domain pairs under two different settings show that Dual-CL achieves better performances than compared baselines in terms of several standard metrics. Moreover, we conduct detailed analyses to are presented to better understand each component’s effectiveness.

Designing computational toys and kits to welcome young children from different genders is essential to broaden participation in computing, as they play a critical role in facilitating children’s development of computational thinking. However, how young learners of different genders are being welcomed by these kits remains unclear. In this paper, we report our in-progress work examining how commercially available coding kits for young children are communicated from a gender perspective. Specifically, we analyzed the gender indications in the product descriptions and advertisement images of 30 kits, revealing a relatively balanced gender representation in images while significantly boy-oriented use of words in product descriptions. Ultimately, we call for attention and actions to more gender-inclusive communication of STEM toys for children.

Physical play has often been leveraged to provide children with active and engaging learning experiences. However, coding activities are predominantly sedentary in front of the screen, and the application of physical play in Computer Science education is less explored, e.g., how can we engage in computational thinking (CT) through physical play? In this design-based exploration, we conducted three design activities where young children, college students, and researchers were invited to create physical play projects using the BBC micro:bit and reflect on their experiences. By examining participants’ projects and creating processes, we provide empirical evidence that remixing physical play activities with coding can engage learners in various CT concepts and practices, reveal how CT concepts and practices can be represented in physical play, and highlight implications for designing physical play-mediated computational learning experiences. Ultimately, we encourage more learning experiences to incorporate physical play into computing education for children.

Identifying cell types is a primary objective in single-cell RNA sequencing (scRNA-seq) analysis, and clustering is a widely used method for achieving this goal. However, the abundance of data and the presence of noise pose significant challenges for single-cell clustering. We propose a novel method called scGCNClustering, which leverages a deep graph convolution network (GCN) with attention. scGCNClustering comprises two core models. The first model is a deep GCN encoder that effectively preserves both the topological structure and feature information in scRNA-seq data, enabling accurate cell segregation. Additionally, we incorporate an attention module into the GCN encoder to capture precise global similarities between cells. The second model is a deep zero-inflated negative binomial (ZINB) decoder, which approximates the true distribution of scRNA-seq data. Extensive analysis conducted on six real scRNA-seq datasets demonstrates that scGCNClustering achieves promising performance in scRNA-seq clustering.

Computational toys and apps, or coding kits, are the primary learning media for young children to engage in Computational Thinking concepts and skills. However, how coding kits are designed to welcome children of different genders remains unclear, a critical research gap given that computing is mostly a male-dominated field. Drawing on relevant literature, we develop a framework of gender-related design features in toys (i.e., boy-oriented, girl-oriented, or gender-neutral features) and employ it to examine gender-related design features in commercially available coding kits for young children aged seven and under (N=110). The findings reveal the lopsided gender representation in coding kits, e.g., their physical forms and supported coding activities are predominantly boy-oriented. We discuss design and research implications for coding kits to welcome participation from children of different genders, especially young girls whose preferred design features are underrepresented in current designs.

HCI researchers have been investigating family dynamics with new and emerging technologies during joint media engagement (JME) experiences. However, most studies describe family dynamics from parents’ perspectives, such as their roles and mediation practices, while the roles and agency of other family members are less understood. In this paper, we examine family dynamics through the lens of negotiation between family members. Our study is located within an informal learning program called Family Creative Learning, where families from non-dominant groups were invited to participate in a series of workshops to create with a programming app called ScratchJr. Through analysis of data that included process, artifact, and reflective data, we identify negotiation practices of family members as they advocate for device and creative control. We further discuss how the lens of negotiation expands the meaning of productive JME in family contexts and highlight design considerations to facilitate engaging joint family experiences with educational technologies.

Technology plays an increasingly pivotal role in mediating mental health support in people's everyday lives. However, it is not clear how that mediation is occurring, to what end, and what technologies are implicated. In this study, we examine these questions with a mixed-methods analysis of conversations among participants in several Bipolar Disorder (BD) communities on Reddit. Analyzing posts produced over four years, we identify a wide variety of technologies that people employ to manage their mental conditions, such as communication technologies, online communities and tracking tools. Using this taxonomy of technologies as a framework, we then summarize three technology-mediated management strategies that these technologies enable, including serving as community, episode, and information mediators. We argue that with a comprehensive and nuanced understanding of people's in situ technology use, we can identify research and design opportunities for designing human-centered technologies to help people manage mental health challenges more effectively.

To inform the design of personally meaningful computational learning experiences for young people, it is necessary to investigate children’s perceptions of coding, such that new learning experience designs can better leverage their funds of knowledge. We conducted focus groups with 20 young children in two coding workshops to learn their perceptions of coding. The young participants mainly form their perceptions of coding based on past coding- and computer-related experiences and typically associate coding with controlling the computer, creating projects, expressing ideas, playing video games, and the language for communicating with the computer. Importantly, young children might not know the right strategies to debug code but try practices like restarting the device and deleting the whole code. Based on the findings, we highlight the pedagogical implications to design productive computational learning experiences for young people.

Parental mediation literature is mostly situated in the contexts of television, Internet use, video games, and mobile devices, while there is less understanding of how parents mediate their children’s engagement with educational-focused media. We examine parental involvement in young children’s use of a creation-oriented educational media, i.e., coding kits, from a mediation perspective through an interview study. We frame parents’ mediation practices along three dimensions: (1) creative mediation, where parents mediate to support children’s creating and learning with media; (2) preparative mediation, where parents explore and prepare media for children’s engagement; and (3) administrative mediation, where parents administer and regulate their children’s media use. Compared to the restrictive, active, and co-using mediation theory, our proposed framework highlights various supportive practices parents take to help their children learn and create with media. We further connect our findings to Joint Media Engagement and reflect on implications for parent involvement in children’s creation-oriented media design.

The COVID-19 pandemic has dramatically shifted family life across home, work, and education, especially families from nondominant groups. As schools and other educational programs moved online, parents became the primary facilitators for their children's learning. In this work, we conducted semi-structured interviews with 22 parents from nondominant groups. Insights from interviews highlight the technology-based learning experiences of young children during the pandemic, how parents facilitated these learning experiences, and the challenges parents and children encountered in these learning experiences. We summarize four parental facilitation patterns for children's learning (i.e., designing learning, finding resources, managing, and teaching) and highlight equity issues in distance learning, such as unequal access to learning resources and quality education. Finally, we further reflect on potential solutions to address the challenges parents have reported and share implications for designing technologies that better address children's and parents' needs during a crisis.

As education researchers, policymakers, and industry leaders recognize the importance of computing, many coding kits (toys and apps) have emerged to help young children learn to code at home. However, how parents perceive and support their children's use of the kits at home are less understood. In this study, we performed semi-structured interviews with eighteen parents who obtained coding kits for their young children for home use. The results show parents expected their kids to have fun and meaningful interactions with the kits. In supporting the play, parents took on various roles, mostly acting as spectator, scaffolder, and teacher. While parents perceived benefits of coding kits like a changed perspective on coding, they also reported concerns, such as their limited programming knowledge to provide help. Finally, we reflect on design and research implications to develop coding kits that consider parents' perspectives and important roles in supporting young children's exploration with computational thinking.

Many toys and kits have been developed to help cultivate computational thinking in young children in the past decade. However, a majority of these kits ask children to move a robot/character around a limited space, constraining what could otherwise be generative and creative learning experiences into pre-defined activities and challenges with uniform outcomes. How can we expand what children can program and how they can create code? In this work, we present CodeAttach, a learning kit designed to engage young children in computational thinking through physical play activities. CodeAttach consists of three parts: (1) an interactive hardware device, (2) a mobile application to program the device, and (3) supporting materials for different play activities. With CodeAttach, children can attach the device to the supporting materials or other everyday objects to create their own props for physical play. The device offers different inputs and outputs and supports children to change the rules of existing physical activities or create new activities by programming this device. We outline the principles guiding the design of CodeAttach, its initial development process, and insights from early playtest with young kids and expert researchers.

This paper presents a survey of computational kits that enable young children (ages 7 years old and under) to explore computing ideas and practices. We examined physical, virtual, and hybrid kits across three different perspectives: how they are designed, how they support children to explore computational concepts and practices, and how they enable children to engage in a range of projects and activities. Based on our analysis, we present design suggestions and opportunities to expand the possibilities in how children can engage in computing, what kinds of projects children can make, and what kinds of computational ideas children can explore.