Understanding Emotional Closeness in Distanced Intergenerational Relationships Between Young Children and Older Adults: A Scoping Review for HCIEmotional closeness (EC) is central to family relationships, however in Human-Computer Interaction (HCI) it is often regarded as self-evident, invoked through adjacent constructs such as connection or co-presence. This ambiguity is particularly limiting for remote relationships between young children (aged 4-8 years) and their older relatives, where developmental asymmetries and generational roles shape how EC unfolds. To clarify how EC is understood in this specific intergenerational context, we conducted a scoping review of 30 papers (2010 - 2025) examining how EC is defined, evaluated, and technologically mediated. Our analysis reveals three key patterns: reliance on self-report evaluations, a persistent interaction-closeness assumption, and under-exploration of embodied and cultural framings. We synthesise a multidimensional definition of EC comprising Affective Expression, Relational Practices, Embodied Presence, and Cultural Belonging. We conclude with implications for HCI, including the need for multimodal and longitudinal methods and technologies that support multi-dimensional, culturally grounded, and meaningful intergenerational connection.2026YWYuehao Wang et al.Queensland University of TechnologyEmpathy & Emotional DesignRemote Family ConnectionChild-Computer Interaction DesignCHI
Influencers vs. Legacy Media on Instagram: Effects on Perceived Credibility and Following IntentionSocial media has blurred the line between professional journalism and personality-driven commentary, yet we know little about how users evaluate credibility and engage with news from influencers and legacy media when they appear in the same feed. This short paper investigates how political ideology and news source type shape perceived credibility and follow intentions on Instagram. We conducted a mixed-methods experiment where U.S.-based participants (N=120) viewed a set of real news posts and rated the credibility of four accounts (two legacy media–based, two influencer-based), balanced by ideology (two eft-leaning, two right-leaning), and indicated whether they would follow each account. Our findings suggest that perceived credibility on Instagram is multi-dimensional, rooted in ideological alignment, yet moderated by institutional signals and perceived authenticity. These insights highlight how platform design and source dynamics can reinforce selective exposure, with implications for both mitigating polarisation and strengthening trust in online news ecosystems.2026CSCherie Sew et al.University of MelbourneSocial Platform Design & User BehaviorContent Moderation & Platform GovernanceMisinformation & Fact-CheckingCHI
Timing Matters: Designing Effective Corrections for Short-Form Video MisinformationShort-form video platforms have become major channels for misinformation, with their rich multimodal features making false claims highly believable. HCI research shows that providing corrections in the same modality as the misinformation can be an effective solution. However, since corrections and misinformation convey contradicting information, the order in which one is exposed to them can impact what one believes. We conducted a between-subjects mixed-methods experiment where participants (N=120) rated the credibility of misinformation statements before and after viewing misinformation videos paired with correction videos. Corrections were shown either before, during, or after misinformation. Across all three timings, corrections reduced belief in misinformation, but post-exposure corrections proved most effective and mid-exposure corrections least effective. These findings suggest that correction mechanisms should appear after misinformation exposure, while avoiding mid-exposure interruptions that reduce impact. We outline design recommendations for integrating correction videos into short-form video platforms to improve resilience against misinformation.2026SGSuwani Gunasekara et al.University of MelbourneMisinformation & Fact-CheckingSocial Platform Design & User BehaviorCHI
“My Tummy Has a Little Dragon”: From Everyday Experiences of Gut Sounds to Interoceptive Interaction Design Gastrointestinal sounds are a constant part of human physiology, offering potential insights into digestive functions and everyday bodily awareness. However, these sounds are rarely noticed and often socially stigmatised, remaining underexplored in HCI despite calls to recognise the gut as a site for embodied awareness. We extend HCI’s engagement with involuntary biosignals by positioning gut sounds as a uniquely generative context for interoceptive interaction design, where systems can scaffold awareness, reflection, and care. We conducted a week-long in-the-wild qualitative study with ten participants, which showed how making gut sounds audible reshaped bodily awareness, provoked affective responses, and prompted acts of reflection and tinkering. From these insights, we contribute four bodily perspectives – Registering, Reacting, Reflecting, and Responding- that capture the oscillatory nature of interoceptive engagement and offer design strategies that position biosignals as sites of curiosity, care, and awareness that are socially situated.2026NPNandini Pasumarthy et al.Monash UniversityEmotion-Sensing WearablesBehavior Change & Reflection TechnologyEmpathy & Emotional DesignCHI
Mapping the Landscape of Affective Extended Reality: A Scoping Review of Biodata-Driven Systems for Understanding and Sharing EmotionsThis paper introduces the notion of affective extended reality (XR) to characterise XR systems that use biodata to enable understanding of emotions. The HCI literature contains many such systems, but they have not yet been mapped into a coherent whole. To address this, we conducted a scoping review of 82 papers that explore the nexus of biodata, emotions, and XR. We analyse the technologies used in these systems, the interaction techniques employed, and the methods used to evaluate their effectiveness. Through our analysis, we contribute a mapping of the current landscape of affective XR, revealing diversity in the goals for enabling emotion sharing. We demonstrate how HCI researchers have explored the design of the interaction flows in XR biofeedback systems, highlighting key design dimensions and challenges in understanding emotions. We discuss underused approaches for emotion sharing and highlight opportunities for future research on affective XR.2026ZLZhidian Lin et al.RMIT UniversityImmersion & Presence ResearchEmotion-Sensing WearablesAffective Human-Computer DialogueCHI
AI Sensing and Intervention in Higher Education: Student Perceptions of Learning Impacts, Affective Responses, and Ethical PrioritiesAI technologies that sense student attention and emotions to enable more personalised teaching interventions are increasingly promoted, but raise pressing questions about student learning, wellbeing, and ethics. In particular, students’ perspectives about AI sensing-intervention in learning are often overlooked. We conducted an online mixed-method experiment with Australian university students (N=132), presenting video scenarios varying by whether sensing was used (in-use vs. not-in-use), sensing modality (gaze-based attention detection vs. facial-based emotion detection), and intervention (by digital device vs. teacher). Participants also completed pairwise ranking tasks to prioritise six core ethical concerns. Findings revealed that students valued targeted intervention but responded negatively to AI monitoring, regardless of sensing methods. Students preferred system-generated hints over teacher-initiated assistance, citing learning agency and social embarrassment concerns. Students’ ethical considerations prioritised autonomy and privacy, followed by transparency, accuracy, fairness, and learning beneficence. We advocate designing customisable, social-sensitive, non-intrusive systems that preserve student control, agency, and well-being.2026BHBingyi Han et al.University of MelbourneBrain-Computer Interface (BCI) & NeurofeedbackExplainable AI (XAI)Mental Health Apps & Online Support CommunitiesCHI
I Can SE Clearly Now: Investigating the Effectiveness of GUI-based Symbolic Execution for Software Vulnerability DiscoveryWhile symbolic execution (SE) can discover software vulnerabilities, it has received limited practical adoption. A key barrier is that SE requires human expertise to understand the program’s state and prioritize paths to analyze. Traditionally, users controlled SE through programmatic API calls, but recent tooling now implements graphical user interfaces (GUI). However, it is unclear how these new features affect human-SE performance. To understand this impact, we conducted a controlled experiment where 24 vulnerability discovery experts were tasked with analyzing a binary using an SE tool with either API or GUI-based features. From this study, we identify (1) experts' SE process, and (2) the impact of GUI-based features on human-SE performance. Then we propose recommendations to improve SE tool design.2026YLYi Jou Li et al.Arizona State UniversityComputational Methods in HCIUser Research Methods (Interviews, Surveys, Observation)Prototyping & User TestingCHI
Gaze and Speech in Multimodal Human-Computer Interaction: A Scoping ReviewMultimodal interaction has long promised to make interfaces more intuitive and effective by combining complementary inputs. Among these, gaze and speech form a compelling pairing: gaze provides rapid spatial grounding, while speech conveys rich semantic information. Together, they offer rich cues for understanding user behaviour and intent. Yet despite decades of exploration, the research remains fragmented, making this synthesis timely as these inputs mature and are integrated into consumer-ready devices. This scoping review examined 103 studies published between 1991 and 2025, organised into \emph{explicit}, where users intentionally provide gaze and speech, and \emph{implicit}, where systems leverage users' natural behaviours to support interaction. Across both, we identified recurring ways for combining gaze and speech to resolve ambiguity, ground references, and support adaptivity. We contribute a synthesis of research on their combined use while highlighting challenges of temporal alignment, fusion and privacy, offering guidance for future research toward richer multimodal human-computer interaction.2026AKAnam Ahmad Khan et al.KAISTEye Tracking & Gaze InteractionVoice User Interface (VUI) DesignAffective Human-Computer DialogueCHI
Plotania: Exploring Transparency Trade-offs in AI Co-Writing Through Virtual Readers and Transparent AttributionCurrent AI writing tools aim to enhance authorial capacity yet often diminish authorial control and lack timely audience feedback. Through a formative study with fiction authors (N=10), we uncovered two critical tensions in human–AI co-writing: balancing AI scaffolding with authorial ownership, and the absence of contextual audience perspectives that shape storytelling during drafting. Guided by these insights, we designed Plotania, a co-writing system that combines proactive virtual readers offering real-time audience reactions with transparent attribution layers. A controlled study (N=20) revealed complex and counterintuitive effects: virtual reader feedback increased audience awareness but decreased perceived creative agency, transforming individual authorship into collaborative performance. Transparent attribution raised awareness of AI contributions but triggered identity anxiety and reduced AI usage. These findings reveal fundamental trade-offs in transparency design. We contribute design principles for "agency-preserving transparency" that balance information provision with creative empowerment, informing future transparency design in human-AI creative collaboration.2026YHYufeng Hu et al.Tsinghua UniversityHuman-LLM CollaborationAI-Assisted Writing & Text GenerationCreative Collaboration & Feedback SystemsCHI
Applying Value Sensitive Design to Location-Based Services: Designing for Shared Spaces and Local ConditionsLocation-Based Services (LBS) such as ride-sharing, accommodation, food delivery, and location-driven social media platforms entangle digital systems with physical spaces, thereby generating impacts that extend beyond users to others who share the same environments. Existing design approaches struggle to address the dual challenge of value tensions that arise in shared physical spaces and the locality-specific contexts in which LBS operate. To respond, we introduce Location-Aware Value Sensitive Design (LA-VSD), a domain-specific adaptation of VSD tailored to the distinctive characteristics of LBS. LA-VSD guides designers through three heuristics to help (1) identify and prioritise stakeholders through local space-sharing scenarios, (2) adapt empirical methods to capture values and tensions in context, and (3) support value-aligned interactions across both digital and physical layers of the service. Through a case study of e-scooter sharing in Melbourne, Australia, we demonstrate how LA-VSD enables more grounded, context-aware, and actionable design of LBS.2026HKHiruni Nuwanthika Kegalle et al.RMIT UniversityMicromobility (E-bike, E-scooter) InteractionInclusive DesignCommunity Engagement & Civic TechnologyCHI
Grand Challenges around Designing Computers’ Control Over Our BodiesAdvances in emerging technologies, such as on-body mechanical actuators and electrical muscle stimulation, have allowed computers to take control over our bodies. This presents opportunities as well as challenges, raising fundamental questions about agency and the role of our body when interacting with technology. To advance this research field as a whole, we brought together expert perspectives in a week-long seminar to articulate the grand challenges that should be tackled when it comes to the design of computers’ control over our bodies. These grand challenges span technical, design, user, and ethical aspects. By articulating these grand challenges, we aim to begin initiating a research agenda that positions bodily control not only as a technical feature but as a central, experiential, and ethical concern for future human–computer interaction endeavors.2026FMFlorian 'Floyd' Mueller et al.Monash UniversityElectrical Muscle Stimulation (EMS)Brain-Computer Interface (BCI) & NeurofeedbackEmpathy & Emotional DesignCHI
Academics’ Reflections on Delivering Hybrid Lessons Through the Analytical Language of Seams and PatchworkThis paper presents insights from a series of interviews with academics at a public university in Ecuador, exploring their experiences in transitioning to synchronous hybrid teaching during the COVID-19 pandemic. This study reveals the challenges faced by academics in navigating the cultural, infrastructural, and technological seams present in the delivery of hybrid lessons in a country in the Global South. The findings provide empirical evidence of the invisible work undertaken by academics to address these challenges, the importance of providing adequate supports for academics when adopting hybrid learning, and the role of student agency in these settings. Finally, we reflect on the implications of deploying hybrid learning for academics' pedagogical practice. By applying the analytical language of seams and patchwork, the study sheds light on the complexities of hybrid learning implementation in a context marked by socio-economic and technological constraints.2025RARonny Andrade et al.Enhancing LearningCSCW
"Nuisance is Better Than Nothing?": Exploring How Pedestrians and Cyclists Perceive Automated E-Scooter Alerts in Shared SpacesElectric scooters (e-scooters) offer flexible urban mobility but raise safety concerns in shared spaces. This study investigates how e-scooters can better communicate their presence to pedestrians and cyclists in shared active mobility environments. A focus group with e-scooter riders identified notifying others of arrival as a key challenge. To address this, we co-designed audio and visual alerts in a participatory workshop and evaluated them in a real-world Wizard of Oz (WoZ) study involving live encounters. WoZ self-report data showed that voice and bell alerts were rated significantly higher in visibility, safety, communication, and acceptance than continuous sounds and flashing lights. These findings were supported by video analysis, which captured clear spatial responses such as turning or moving aside. Cyclists rated alerts as more distracting than pedestrians. Eye-tracking data revealed increased pedestrian attention during overtaking. By combining self-reports, video, and gaze data, we provide in-situ evidence and design recommendations to improve e-scooter signalling and reduce conflict. The dataset, including anonymized ratings, fixation data, alert designs, and analysis scripts, is available at https://github.com/HiruniNuwanthika/User-Perception-Evaluation-Escooter-Alerts.git.2025HKHiruni Nuwanthika Kegalle et al.External HMI (eHMI) — Communication with Pedestrians & CyclistsMicromobility (E-bike, E-scooter) InteractionMobileHCI
MindEat!: Navigating Screen-Centric Dining through Mindful Technology DesignIn an era where technology pervades every aspect of our daily lives, including dining, we grapple with the challenge of harmonizing its immersive nature with the ethos of mindful eating. Despite some strides in designing technologies to support mindful eating, existing efforts remain fragmented and lack a comprehensive grasp of the intricate factors essential for cultivating such dining experiences. This pictorial introduces MindEat! an inventive design framework tailored for designers embarking on the development of technologies that support mindful eating experiences. Similar to the layered composition of a culinary sandwich, each component of this framework encompasses a distinct aspect of mindful eating, deserving careful consideration throughout the design process. By emphasizing metaphorical engagement with mindful eating principles, and practical application in the design process, this framework aims to contribute to the creation of enjoyable health-promoting solutions that resonate with the realities of screen-centric dining cultures.2025RKRohit Ashok Khot et al.Mental Health Apps & Online Support CommunitiesSustainable HCIFood Culture & Food InteractionDIS
The Impact of Human-Likeness and Self-Disclosure on Message Acceptance in Virtual AI InfluencersVirtual AI-generated Influencers (VAIIs) are increasingly being used by corporations and public agencies, raising questions about how their visual design and communication strategies impact end-users' propensity to accept the messages they deliver. We examined the impact of human-likeness (how close the VAII visually resembles a human) and self-disclosure (whether the message contains personal information) on message acceptance, alongside dispositional factors like empathy and anthropomorphising tendencies. In a mixed-methods experiment, participants (N=120) watched short-form videos featuring VAIIs of varying human-likeness (High/Moderate-High/Moderate-Low/Low) and self-disclosure (present/absent). We observed the strongest message acceptance from the VAIIs with the lowest human-likeness, and message rejection for VAIIs with moderate to low human-likeness. Additionally, participants' message acceptance was influenced by their empathy tendencies. Our qualitative analysis revealed further insights into participants' perceptions of the human-likeness of VAIIs, their discomfort with self-disclosure, and their tendency to anthropomorphise VAIIs. These findings provide important implications for the design of VAIIs.2025CSCherie Sew et al.Agent Personality & AnthropomorphismGenerative AI (Text, Image, Music, Video)DIS
The Brain Knows What You Prefer: Using EEG to Decode AR Input PreferencesUnderstanding user input preferences is crucial in immersive environments, where input methods such as gestures and controllers are common. Traditional evaluation methods rely on post experience questionnaires, which don't capture real-time preferences. This study used brain signals to classify input preferences during Augmented Reality (AR) interactions. Thirty participants performed three interaction tasks (pointing, manipulation, and rotation) using hands or controllers. Their electroencephalogram (EEG) data were collected at varying task difficulties (low, medium, high) and phases (preparation, task, and completion). Machine learning was used to classify preferred and non-preferred input methods. Results showed that EEG signals effectively classify preferences with accuracies up to 86%, with the completion phase being the best indicator of preference. In addition, different input methods exhibited distinct EEG patterns. These findings highlight the potential of EEG signals for decoding real-time input preference in AR, offering insights for enhancing user experiences.2025KZKaining Zhang et al.University of South Australia, Empathic Computing LabBrain-Computer Interface (BCI) & NeurofeedbackAR Navigation & Context AwarenessCHI
“They’re Scamming Me”: How Children Experience and Conceptualize Harm in Game MonetizationRegulatory shifts are increasingly placing the onus on online service providers such as digital game developers and platforms to ensure that their services do not harm children. This creates an urgent need to examine how children experience and conceptualize harm in digital contexts, which may differ from adult-driven perceptions of harm. In this paper, we present the results of a study into children’s experiences with game monetization which included a ‘think-aloud’ method in which children were given an AU$20 voucher to spend. Through our participants’ (aged 7-14) vernacular of feeling ‘scammed’ or ‘tricked’, we argue that children experience harm principally through being misled or deceived by monetization features, rather than being due to what parents perceive as a misattribution of value toward digital items or overspending. Based on these results, we make game design recommendations to minimize children’s harmful experiences with game monetization strategies.2025THTaylor Hardwick et al.The University of SydneyUniversal & Inclusive DesignGamification DesignGame AccessibilityCHI
Educator Perceptions of XRAuthor: An Accessible Tool for Authoring Learning Content with Different Immersion LevelsThe promise of Extended Reality (XR) in education is significant but one size does not fit all learning contexts and student preferences. Varied content with different immersion levels is hence beneficial, but creating XR content remains daunting for educators using conventional tools. This paper introduces XRAuthor, a web-based authoring tool designed to empower educators to create varying immersive learning content - ranging from conventional video to interactive animations and full-fledged VR - all from a single authoring experience with a webcam. Through online one-to-one workshops with 14 educators, we found strong endorsement for the new authoring workflow enabled by XRAuthor. Participants also found that the varied interactive exercises automatically generated by the tool aligned well with effective pedagogical practices. High ease of use and efficiency were identified as crucial attributes of XRAuthor. The design knowledge facilitated by XRAuthor underscores the potential of such tool designs to democratize XR content creation for learning.2025SSSongjia Shen et al.Singapore Institute of Technology, Centre for ImmersificationMixed Reality WorkspacesOnline Learning & MOOC PlatformsCHI
Prevalence and Impacts of Image-Based Sexual Abuse Victimization: A Multinational StudyImage-based sexual abuse (IBSA) refers to the nonconsensual creating, taking, or sharing of intimate images, including threats to share intimate images. Despite the significant harms of IBSA, there is limited data on its prevalence and how it affects different identity or demographic groups. This study examines prevalence of, impacts from, and responses to IBSA via a survey with over 16,000 adults in 10 countries. More than 1 in 5 (22.6%) respondents reported an experience of IBSA. Victimization rates were higher among LGBTQ+ and younger respondents. Although victimized at similar rates, women reported greater harms and negative impacts from IBSA than men. Nearly a third (30.9%) of victim-survivors did not report or disclose their experience to anyone. We provide large-scale, granular, baseline data on prevalence in a diverse set to aid in the development of effective interventions that address the experiences and intersectional identities of victim-survivors'.2025RURebecca Umbach et al.Google, Trust & Safety ResearchOnline Harassment & Counter-ToolsGender & Race Issues in HCILGBTQ+ Community Technology DesignCHI
The Influence of Content Modality on Perceptions of Online MisinformationSocial media has become a primary information source, with platforms evolving from text-based to multi-modal environments that include images and videos. While richer media modalities enhance user engagement, they also increase the spread and perceived credibility of misinformation. Most interventions to counter misinformation on social media are text-based, which may lack the persuasive power of richer modalities. This study explores whether the effectiveness of misinformation correction varies by modality, and if certain modalities of misinformation are better countered by a specific correction modality. We conducted a survey-based experiment where participants rated the credibility of misinformation tweets before and after exposure to corrections, across all combinations of text, images and video modalities. Our findings suggest that corrections are most effective when their modality richness matches that of the original misinformation. We discuss factors affecting the perceived credibility of corrections and offer strategies to optimise misinformation correction.2025SGSuwani Gunasekara et al.University of Melbourne, School of Computing and Information SystemsContent Moderation & Platform GovernanceMisinformation & Fact-CheckingCHI