Beyond domestication: Differentiating mental models from primary and secondary users in smart home lighting systemsCommonly attributed smart home challenges for both primary and secondary users have been researched extensively, yet there is a gap in understanding mental models and their influence on how both types of users internalize and domesticate smart home lighting systems including bulbs, lamps, smart plugs, switches, and presence sensors. Our study targets the perceptual distinction between both users from a long-term domestication perspective. We conducted an in-situ ethnographic study with 12 households in the Netherlands and a subsequent online survey with 93 participants. Our research offers three contributions. By analyzing guided diaries, interviews, and surveys, we characterize the intricate mental models (spatial, contextual, functional, and metaphorical mapping) within and across households. Second, we addressed the distinctiveness and importance of the post-domestication phase in smart home lighting systems. Lastly, we present design recommendations to improve future smart home system designs aimed at long-term, evolving use.2026JDJiaxin Dai et al.Signify ResearchSmart Home Interaction DesignSmart Home Privacy & SecurityCHI
Shared Stories, Shared Bonds: People with Dementia Exploring Generative AI TogetherPeople with dementia often experience social isolation in daily life. Generative AI (GenAI) technologies, producing seemingly new content on the spot and tailoring it to users' wishes, open new avenues for promoting meaningful social connections in dementia care. This study involved 17 people with dementia in 6 workshops and explored how they responded to and perceived three GenAI models, Copilot, Midjourney, and Suno, with a focus on social connectedness. Our results reveal that people with dementia engage in a relational process when using GenAI together: they collectively evaluate the outcomes of the models and negotiate further prompts. Moreover, they gradually develop an understanding of GenAI and become more critical about its output. We contribute to HCI by demonstrating how GenAI can foster social bonding between people with dementia through the co-creation of shared realities, and by discussing guidelines for designing effective and ethically responsible GenAI for people with dementia.2026TATeis Arets et al.Eindhoven University of TechnologyGenerative AI (Text, Image, Music, Video)Elderly Care & Dementia SupportEmpowerment of Marginalized GroupsCHI
Conversing with Objects toward Fluid Human and Artificial Identities during Life TransitionsPeople's identities change during life transitions (e.g., studying abroad). They bring everyday objects that embody memories and reflect their identities during such moves. To assist in these transitions, we ask how people's human identities could be supported by their objects through an artificial agent. This paper presents an exploratory research-through-design study around how people undergoing life transitions experience conversing with their everyday objects through a chatbot. Drawing on a two-week field deployment of a technology probe and interviews with 12 participants, we contribute (1) a conceptualization of "trans-embodiment" describing the asynchronous imagination of object and human identities on the chatbot, (2) empirical evidence of the resulting trans-embodied emotional and reflective experiences that supported identity processes, and (3) three types of trans-embodied object identities for designing conversational agents for human-object conversations. Our contributions sum up to triangulating human-agent-object identity as trans-embodiment in supporting life transitions.2026YXYuhui Xu et al.Eindhoven University of TechnologyConversational ChatbotsAffective Human-Computer DialogueEmpathy & Emotional DesignCHI
Staring at Tables: Exploring Conceptual Data Modeling as a Rich Collaborative ActivityConceptual data modeling is a central activity in data work, yet how such models are created remains understudied. While data attributes play a key role, modeling is also shaped by tasks, tools, developers’ prior experiences, and often unfolds collaboratively between diverse stakeholders. In this study, we invited 22 participants with varying expertise in pairs to collaboratively sketch conceptual data models. We captured screen recordings, their evolving sketches, and conversations. Through a mixed-methods approach combining thematic analysis of dialogue with an examination of model artifacts, we identify how communication and collaboration patterns influenced the process. Our findings reveal a range of collaborative strategies and representations, as well as distinct ways dialogue shaped the emergence and expression of shared conceptual models. These insights deepen understanding of Human-Data Interaction in collaborative data work and point to design opportunities for tools that better support communication, negotiation, and sensemaking of data.2026LKLaura Koesten et al.Mohamed bin Zayed University of Artificial IntelligencePrototyping & User TestingCrowdsourcing Task Design & Quality ControlKnowledge Management & Team AwarenessCHI
In-person, Online and Back Again - A Tale of Three Hybrid HackathonsHybrid hackathons, which combine in-person and online participation, present unique challenges for organizers and participants. Although these events are increasingly conducted globally, research on them remains fragmented, with limited integration between hackathon studies and hybrid collaboration. Existing strategies for in-person or online-only events often fail to address the unique challenges of hybrid formats, such as managing communication across physical and virtual spaces and ensuring balanced participation. Our work addresses this gap by examining how hybrid hackathons function through the lens of hybrid collaboration theories, analyzing how organizers structure these events and how participants navigate hybrid-specific challenges. Drawing on established theories of hybrid collaboration, we examine key dimensions -- synchronicity, physical distribution, dynamic transitions, and technological infrastructure -- that shape collaboration in hybrid events. Through an exploratory case study of three hackathon events involving observations and interviews with organizers and participants, we analyze how these dimensions are implemented and their effects on participant experiences. Our findings reveal differing organizer considerations of the hybrid dimensions in the hackathon design, leading to distinct experiences for participants. Implementation styles -- favoring in-person, online, or balanced participation -- led to varied participant experiences, affecting access to resources, communication, and team coordination. Organizers in our study also often relied on technology to bridge hybrid interactions, but sometimes overlooked critical aspects like time-zone management, dynamic transitions, and targeted support for hybrid teams. Additionally, participants in their teams responded to gaps in event scaffolding by adapting collaboration strategies, underscoring that hybrid formats are still not fully integrated into hackathon planning and revealing gaps in organizers’ preparedness for hybrid events. Learning from our findings, we offer practical recommendations when organizing hybrid hackathon events and recommendations to participants when attending hybrid hackathon events.2025AAAbasi-Amefon Obot Affia et al.Hybrid WorkCSCW
A Review on the Development of the In-Vehicle Human-Machine Interfaces in Driving Automation: A Design PerspectiveThe advancement of automated driving technologies is fundamentally transforming the relationship between humans and vehicles, shifting from direct control to a more collaborative dynamic. Consequently, the design of in-vehicle Human-Machine Interfaces (iHMIs) is becoming increasingly intricate, focusing on aspects beyond mechanics and ergonomics towards enriched interaction and enhanced user experience. This shift has prompted research efforts to explore and advance iHMI concepts. Despite the iterative nature of design and its role in knowledge creation, our high-level understanding of the design processes utilised in iHMI development remains limited. To provide a comprehensive overview, this paper presents a scoping review of 324 papers (2013—2023) focused on the design underpinnings of iHMI development. Our review presents a categorisation of study goals and a detailed classification of five key stages within the design process. Based on these analyses, we discuss the influence of design and identify potential avenues for future research on iHMIs.2024HDHaoyu Dong et al.Automated Driving Interface & Takeover DesignIn-Vehicle Haptic, Audio & Multimodal FeedbackAutoUI
Designing for Interdependence of Bees, Garden, Designer, and the Changing SeasonThe speculation of alternative relationships between humans and nonhumans is a crucial element of examining our dominating stance towards nature amidst the ongoing environmental crisis. The notion of designing for interdependence challenges this status quo, focusing on a local ecosystem and embedding carefully crafted artefacts to foster more-than-human relationships. The presented work engages with the intricate interdependence of bees, artefacts, time and location through an ongoing case study of designing with and living with red mason bees (Osmia bicornis). Unpacking the first author’s design journey, we elucidate how attentive observations of the garden and engagement in activities such as the making of a beehouse have mobilized caring for the local ecosystem. With our focus on relationships emerging from situating oneself in a location for multispecies cohabitation, our research describes the dynamics of sharing resources between humans and nonhumans and its potential as a repertoire of more-than-human design.2024YIYuta Ikeya et al.Sustainable HCIHuman-Nature Relationships (More-than-Human Design)DIS
Competencies for Code ReviewPeer code review is a widely practiced software engineering process in which software developers collaboratively evaluate and improve source code quality. Whether developers can perform good reviews depends on whether they have sufficient competence and experience. The lack of competencies can stand in the way of efficient code reviews. However, the knowledge of what competencies developers need to execute code review is currently limited, thus hindering, for example, the creation of effective support tools and training strategies. To address this gap, we firstly identified 27 competencies relevant to performing code review through expert validation. Later, we conducted an online survey with 105 reviewers to rank these competencies along four dimensions: frequency of usage, importance, proficiency, and desire of reviewers to improve in that competency. The survey shows that technical competencies are considered essential to performing reviews and that respondents feel generally confident in their technical proficiency. Moreover, reviewers feel less confident in how to communicate clearly and give constructive feedback - competencies they consider like-wise an essential part of reviewing. Therefore, research and education should focus in more detail on how to support and develop reviewers’ potential to communicate effectively during reviews. In the paper, we also discuss further implications for training, code review performance assessment, and reviewers of different experience level.2023PGPavlína Wurzel Gonçalves et al.Workplace IICSCW
Models of (Often) Ambivalent Robot Stereotypes: Content, Structure, and Predictors of Robots' Age and Gender StereotypesThis study focused on investigating the content, structure, and predictors of robots' stereotypes. We involved 120 participants in an online study and asked them to rate 80 robots on communion, agency, suitability for female and suitability for male tasks. In line with the stereotype content model, we discovered that robots' stereotypes are described by two dimensions, communion and agency, which combine to form univalent (e.g., low communion/low agency), as well as ambivalent clusters (e.g., low communion/high agency). Moreover, we found out that a robot’s stereotypical appearance has a role in activating stereotypes. Indeed, in our study, female robots featuring appearance cues socio-culturally associated with femininity (e.g., eyelashes or apparel) were perceived as more communal, and juvenile robots featuring appearance cues tapping into the baby schema (e.g., cartoony eyes) were perceived as more communal, less agentic, and less suited to perform tasks. Given the renowned relationship between stereotyping, prejudice and discrimination, the causal link between appearance and stereotyping we establish in this paper can help HRI researchers disentangle the relation between robots' design and people's behavioral tendencies towards them, including proneness to harm.2023GPGiulia Perugia et al.Social Robot InteractionAlgorithmic Fairness & BiasGender & Race Issues in HCIHRI
Towards Guidelines for Designing Human-in-the-Loop Machine Training InterfacesSupervised machine learning approaches commonly require good availability and quality of training data. In applications that depend on human-labeled data, especially from experts, or that depend on contextual knowledge for training data sets, the human-in-the-loop presents a serious bottleneck to the scalability of training efforts. Even if human labeling is generally feasible, sustained human performance and high-quality labels in larger quantities are challenging. Interactive Machine Learning can help solve usability problems in traditional machine learning by giving users agency in deciding how systems learn from data. Yet, the field lacks clear design guidelines for such interfaces, specifically regarding the scaling of training processes. In this paper, we present results from a pilot study in which participants interacted with several interface variants of a recommender engine and evaluated them on interaction and efficiency parameters. Based on the performance of these different learning system implementations we propose design guidelines for the design of such systems and a score for comparative evaluation, in which we combine interaction experience and system learning efficiency into one relative scoring unit.2021ASAlmar van der Stappen et al.Human-LLM CollaborationExplainable AI (XAI)AI-Assisted Decision-Making & AutomationIUI
Expressivity in Interaction, a Framework for DesignExpressivity is frequently recurring as a term in HCI, but it is often approached from different perspectives. Affective computing prompted research into emotional expressivity, and with technology becoming more ubiquitous and tangible, the opportunities for expressive behaviors towards systems as well as the expressivity of systems increases. By analyzing exemplar research-through-design cases and a literature survey on the use of expressivity in interaction, we discuss how different perspectives and concepts contribute to understand expressivity in interaction. We integrate these perspectives and make them operational for interaction design by creating a framework including design considerations such as freedom of interaction, action-perception loops, multimodality, subtlety, ambiguity, skill development and temporal form. The framework is a result of a mixed-method approach including a review of existing definitions and scholarly artefacts, and a systematic literature review to identify design cases including an analysis of these design cases. We finally illustrate how the framework has been used to inform the design of a shape-changing soft-robotic interface. As a result, we contribute an integrated framework on how to design for expressivity in interaction.2021MBMiguel Bruns et al.TU EindhovenShape-Changing Interfaces & Soft Robotic MaterialsCHI
Designing Haptic Effects on an Accelerator Pedal to Support a Positive Eco-Driving ExperienceHaptic feedback has frequently been proposed as a means to support eco-driving behaviour. While force and vibrotactile feedback have proven to be effective and safe approaches, no studies were found that assessed the user experience of different feedback designs. We describe the design of six haptic effects which were implemented in a custom designed accelerator pedal. The user experience of three effects (linear force increase, bump and pulse) were assessed in a driving simulator and compared to a baseline with no feedback. Results show that the haptic pedal effects were rated positively on attractiveness, dependability, stimulation and novelty. The pulsating effect scored significantly lower on attractiveness and dependability but highest on the novelty. Qualitative results suggest that combining a bump and pulse could increase the positive experience of a haptic pedal. Consequently, we argue for more experiential approaches to haptic feedback design in accelerator pedals.2019ARAlex de Ruiter et al.EV Charging & Eco-Driving InterfacesForce Feedback & Pseudo-Haptic WeightAutoUI
Grand Challenges in Shape-Changing Interface ResearchShape-changing interfaces have emerged as a new method for interacting with computers, using dynamic changes in a device's physical shape for input and output. With the advances of research into shape-changing interfaces, we see a need to synthesize the main, open research questions. The purpose of this synthesis is to formulate common challenges across the diverse fields engaged in shape-change research, to facilitate progression from single prototypes and individual design explorations to grander scientific goals, and to draw attention to challenges that come with maturity, including those concerning ethics, theory-building, and societal impact. In this article we therefore present 12 grand challenges for research on shape-changing interfaces, derived from a three-day workshop with 25 shape-changing interface experts with backgrounds in design, computer science, human-computer interaction, engineering, robotics, and material science.2018JAJason Alexander et al.Lancaster UniversityShape-Changing Interfaces & Soft Robotic MaterialsCHI
Ripple Thermostat: Affecting the Emotional Experience through Interactive Force Feedback and Shape ChangeForce feedback and shape change are modalities with a growing application potential beyond the more traditional GUIs. We present two studies that explored the effect of these modalities on the emotional experience when interacting with an intelligent thermostat. The first study compared visual feedback, force feedback, and a combination of force feedback and shape change. Results indicate that force feedback correlates to experienced dominance during interaction, while shape change mainly affects experienced arousal. The second study explored how force feedback and shape change could communicate affective meaning during interaction with the thermostat through a co-design study. Participants designed the thermostat behavior for three scenarios supporting energy savings. Results suggest that despite their abstractness, force feedback and shape change convey affective meaning during the user-system dialogue. The findings contribute to the design of intelligible and intuitive feedback.2018AOAnke van Oosterhout et al.Aarhus UniversityForce Feedback & Pseudo-Haptic WeightShape-Changing Interfaces & Soft Robotic MaterialsCHI