Hacking Flow: From Lived Practices to InnovationIn digital knowledge work, flow promises not just productivity; it offers a pathway to well-being. Yet despite decades of flow research in HCI, we know little about how to design digital interventions that support it. In this work, we foreground lived interventions — everyday practices workers already use to foster flow — to uncover overlooked opportunities and chart new directions for digital intervention design. Specifically, we report findings from two studies: (1) a reflexive thematic analysis of open-ended survey responses (n = 160), surfacing 38 lived interventions across four categories: environment, organization, task shaping, and personal readiness; and (2) a quantitative online survey (n = 121) that validates this repertoire, identifies which interventions are broadly endorsed versus polarizing, and elicits visions of technological support. We contribute empirical insights into how digital workers cultivate flow, situate these lived interventions within existing literature, and derive design opportunities for future digital flow interventions.2026FSFabio Stano et al.Karlsruhe Institute of Technology (KIT)Knowledge Worker Tools & WorkflowsWorkplace Wellbeing & Work StressBehavior Change & Reflection TechnologyCHI
Exploring the Potential of Disengagement-Friendly Game Design to Support Children's Exit from Play SessionsDisengagement from games is challenging for children, and can lead to family conflict. While parental mediation is well-understood, the role of game design in supporting children’s disengagement remains underexplored. Our work addresses this gap through a qualitative study with 39 participants (22 children aged 4-11 and 17 parents), in which children played Snarky’s Adventure, a prototype featuring disengagement-friendly mechanics supporting player understanding of progress, and the experience of satisfaction and closure at the end of play. Through Qualitative Content Analysis, we show that the features help children anticipate the end of play, but in some cases spark curiosity and the desire to re-engage. Additionally, while parents valued the mechanics to understand game progress, future work should explore how to actively engage them in children’s disengagement. Our work provides the first empirical exploration of disengagement-friendly game mechanics, and outlines challenges and opportunities for their future integration in children's games.2026MAMeshaiel M Alsheail et al.Karlsruhe Institute of TechnologyGame UX & Player BehaviorDigital Parenting & Screen Time ManagementCHI
Why Johnny Checks but Doesn’t Alert: Reporting as the Missing Step in Verifiable Internet VotingEnd-to-end verifiable Internet voting promises that voters can remotely check whether their ballot was recorded correctly and that all ballots were tallied as cast. However, in order to achieve an adequate level of security, voters actually need to perform the first check. Our research focuses on the cast-then-audit approach for this check. We use related work to improve this approach in particular by providing a step-by-step guide. We conducted a deceptive online user study (N=437) to compare our improved system with a baseline version from an actual election. We also measured the usability and participants confidence in using such systems. Our findings show that participants from the improved system perform significantly better than the baseline w.r.t. manipulation detecting and reporting capabilities. Furthermore, we show that it is important to distinguish between detection and reporting to understand how to further increase the overall security.2026THTobias Hilt et al.Karlsruhe Institute of TechnologyPrivacy by Design & User ControlPrivacy Perception & Decision-MakingCybersecurity Training & AwarenessCHI
AttentiveLearn: Personalized Post-Lecture Support for Gaze-Aware Immersive LearningImmersive learning environments such as virtual classrooms in Virtual Reality (VR) offer learners unique learning experiences, yet providing effective learner support remains a challenge. While prior HCI research has explored in-lecture support for immersive learning, little research has been conducted to provide post-lecture support, despite being critical for sustained motivation, engagement, and learning outcomes. To address this, we present AttentiveLearn, a learning ecosystem that generates personalized quizzes on a mobile learning assistant based on learners’ attention distribution inferred using eye-tracking in VR lectures. We evaluated the system in a four-week field study with 36 university students attending lectures on Bayesian data analysis. AttentiveLearn improved learners’ reported motivation and engagement, without conclusive evidence of learning gains. Meanwhile, anecdotal evidence suggested improvements in attention for certain participants over time. Based on our findings of the field study, we provide empirical insights and design implications for personalized post-lecture support for immersive learning systems.2026SLShi Liu et al.Karlsruhe Institute of TechnologyImmersion & Presence ResearchEye Tracking & Gaze InteractionIntelligent Tutoring Systems & Learning AnalyticsCHI
CoEmpaTeam: Enhancing Cognitive Empathy using LLM-based Avatars and Dynamic Role Play in Virtual RealityCognitive empathy, the ability to understand others‘ perspectives, is essential for effective communication, reducing biases, and constructive negotiation. However, this skill is declining in a performance-driven society, which prioritizes efficiency over perspective-taking. Here, the training of cognitive empathy is challenging because it is a subtle, hard-to-perceive soft skill. To address this, we developed CoEmpaTeam, a VR-based system that enables users to train their cognitive empathy by using LLM-driven avatars with different personalities. Through dynamic role play, users actively engage in perspective-taking, experiencing situations through another person's eyes. CoEmpaTeam deploys three avatars who significantly differ in their personality, validated by a technical evaluation and an online experiment (n=90). Next, we evaluated the system through a lab experiment with 32 participants who performed three sessions across two weeks, followed by a one-week diary study. Our results showed a significant increase in cognitive empathy, which, according to participants, transferred into their real lives.2026DKDehui Kong et al.Karlsruhe Institute of Technology (KIT)Brain-Computer Interface (BCI) & NeurofeedbackSocial & Collaborative VRIdentity & Avatars in XRCHI
Characterising Gaming Group ExperiencesWhen people play digital games together, their experiences are often influenced by the group. While prior research has focused on the individual player experience, we argue that a deeper understanding of group dynamics is required for designing digital games that effectively support complex social interactions. In this paper, we characterise the lived group experiences of fifteen long-term players, using qualitative content analysis of semi-structured interviews examining group lifecycles, their impact on play, and how games and platforms support or constrain them. Our findings show that gaming groups are diverse, often shifting between people- and task-orientation based on needs and motivations. They influence how games are experienced, establishing shared practices that persist across contexts. Yet, while games and tools support group play, they often lack flexibility to accommodate such evolving and nuanced social dynamics. We provide insight into how group-based play unfolds and examples of how games can better support it.2026DRDaniel Reis et al.Universidade de LisboaGame UX & Player BehaviorMultiplayer & Social GamesCHI
Do Citizens Agree with the EU AI Act? Public Perspectives on Risk and Regulation of AI SystemsThe European Union (EU) has spearheaded the regulation of artificial intelligence (AI) with the AI Act, which regulates AI systems based on the risks they pose to fundamental rights and other protected values. AI systems that pose unacceptable risks are prohibited, high-risk AI systems must comply with mandatory requirements, and minimal risk AI systems are encouraged—but not required—to adopt voluntary standards. Motivated by concerns that the AI Act may not reflect the public's opinions, we investigate how laypeople (N=1,421) assess 48 different AI systems concerning their risk and regulation. We find that people believe all 48 AI systems pose moderate levels of risk and should be regulated (albeit without outright prohibitions). Our findings challenge the AI Act's tiered approach, showing that people might support horizontal regulation requiring minimal standards for AI systems, and provide implications for developers seeking to develop AI aligned with public expectations.2026GLGabriel Lima et al.Max Planck Institute for Security and PrivacyAI Ethics, Fairness & AccountabilityPrivacy by Design & User ControlPrivacy Perception & Decision-MakingCHI
Rest Assured: Detecting Mental Fatigue and Recovery with EEG HeadphonesMental fatigue, a common consequence of cognitively demanding work, impairs concentration and well-being, posing long-term health risks. Distinct from drowsiness, mental fatigue is reliably measured with EEG, yet conventional setups remain too cumbersome for everyday use. To overcome this barrier, this study investigates whether EEG headphones can detect mental fatigue and recovery across two common digital break activities: playing a video game and browsing social media. We conducted an experiment with consecutive task sessions and an intermittent break, collecting self-report, performance, and EEG data. Our results show that EEG headphones can detect mental fatigue and recovery dynamics via relative alpha power, and differentiate recovery effects between break types. Social media proved more restorative than gaming, with effects persisting into the subsequent task. These findings establish needed working principles for using headphone-EEG in naturalistic fatigue and recovery research, providing a foundation for future studies.2026LSLukas Schick et al.Karlsruhe Institute of Technology (KIT)Brain-Computer Interface (BCI) & NeurofeedbackEmotion-Sensing WearablesBehavior Change & Reflection TechnologyCHI
Rethinking Interdependence in HCI: A Systematic Literature Review for Understanding its Use in Accessibility StudiesInterdependence has long been a core concept in Disability Studies and activism, offering a critical response to dominant ideals of independence. While Bennett et al.’s work introduced interdependence into accessibility research in HCI by linking it with research and design practices, the extent to which HCI has meaningfully engaged with the theoretical and political roots of the concept remains unclear. In this literature review, we systematically analyze 70 HCI accessibility papers that engage with the concept of interdependence. Guided by the PRISMA framework, we investigate how interdependence is conceptualized and applied in HCI, identifying strengths and shortcomings of current conceptualizations. Our findings reveal that interdependence is used across a range of use cases that broaden its scope, but that integration remains partial and fragmented, often disconnected from its origins in Disability Studies and activism. We conclude by calling for a more meaningful integration of interdependence into HCI accessibility research.2026ZYZeynep Yildiz et al.Karlsruhe Institute of TechnologyUniversal & Inclusive DesignCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Visual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)CHI
Development, Evaluation, and Implementation of SEQR -- a Usable Secure QR Code ScannerQR codes are widely used, but can become the vector of phishing attacks (QRishing). To support users, we systematically developed a usable secure QR code scanner, SEQR (Security Enhanced QR code scanner). We based the SEQR's design on two systematic reviews: (i) of academic literature (2015–2025), identifying 96 papers on QRishing, and (ii) of the MITRE ATT&CK® Mobile repository, finding 36 QRishing techniques. From these two sources, we categorized 60 potential attacks, and divided them between those that SEQR addresses only at the technology level, and those where SEQR involves the users in the decision. We evaluated SEQR effectiveness in thwarting attacks in a between-subjects online study (n=556), where SEQR achieved 93.35% correct answers, compared to 75.24% for the Apple iOS QR code scanner and 65.11% for the Samsung Android QR code scanner. We implemented SEQR as an open source Android application, available on GitHub.2026MMMattia Mossano et al.SECUSO, Karlsruhe Institute of Technology (KIT)Privacy by Design & User ControlPasswords & AuthenticationPrivacy Perception & Decision-MakingCHI
Flow on Social Media? Rarer Than You'd ThinkResearchers often attribute social media’s appeal to its ability to elicit flow experiences of deep absorption and effortless engagement. Yet prolonged use has also been linked to distraction, fatigue, and lower mood. This paradox remains poorly understood, in part because prior studies rely on habitual or one-shot reports that ask participants to directly attribute flow to social media. To address this gap, we conducted a five-day field study with 40 participants, combining objective smartphone app tracking with daily reconstructions of flow-inducing activities. Across 673 reported flow occurrences, participants rarely associated flow with social media (2\%). Instead, heavier social media use predicted fewer daily flow occurrences. We further examine this relationship through the effects of social media use on fatigue, mood, and motivation. Altogether, our findings suggest that flow and social media may not align as closely as assumed - and might even compete - underscoring the need for further research.2026MKMichael T. Knierim et al.Karlsruhe Institute of Technology (KIT)Social Platform Design & User BehaviorCyberbullying & Online HarassmentEmpathy & Emotional DesignCHI
Motion-Touch: Kinematic-based Adaptive Switch for Enhancing Virtual-Hand Selection with Target Prediction in AR/VRVirtual hand selection techniques in AR/VR face a persistent challenge due to the inherent speed–accuracy trade-off. Although target prediction offers a promising direction, its practical adoption is limited by the inevitable errors of predictive models. We present Motion-Touch, a selection technique that integrates a Kinematics-Based Adaptive Switch (KBAS) with deep-learning-based target prediction. KBAS switches between the two phases of pointing process: an untriggerable ballistic phase and a corrective phase in which only the AI-predicted target can be triggered through Touch. The technique can adaptively switch between these phases under distinct kinematic conditions. We collected a hand kinematics dataset from 20 participants to support model training and mechanism calibration. Compared to baseline techniques, Motion-Touch achieves selection times statistically comparable to the fastest reliable controller, while offering controller-free, error-free selection with minimal trigger effort. Our findings demonstrate how Motion-Touch achieves a near-optimal compromise for the speed–accuracy trade-off in virtual hand selection.2026YLYixuan Liu et al.Southern University of Science and TechnologyImmersion & Presence ResearchFull-Body Interaction & Embodied InputEye Tracking & Gaze InteractionCHI
Human Delegation Behavior in Human-AI Collaboration: The Effect of Contextual InformationThe integration of artificial intelligence (AI) into human decision-making processes at the workplace presents both opportunities and challenges. One promising approach to leverage existing complementary capabilities is allowing humans to delegate individual instances of decision tasks to AI. However, enabling humans to delegate instances effectively requires them to assess several factors. One key factor is the analysis of both their own capabilities and those of the AI in the context of the given task. In this work, we conduct a behavioral study to explore the effects of providing contextual information to support this delegation decision. Specifically, we investigate how contextual information about the AI and the task domain influence humans' delegation decisions to an AI and their impact on the human-AI team performance. Our findings reveal that access to contextual information significantly improves human-AI team performance in delegation settings. Finally, we show that the delegation behavior changes with the different types of contextual information. Overall, this research advances the understanding of computer-supported, collaborative work and provides actionable insights for designing more effective collaborative systems.2025PSPhilipp Spitzer et al.Working with AICSCW
Delusionized? Potential Harms of Proprioceptive Manipulations through Hand Redirection in Virtual RealityTo enhance interactions in VR, hand redirection (HR)-based illusion techniques apply offsets between the virtual and real-world position of users’ hands. While adaptation to such HR offsets is recognized, their impact on proprioception accuracy remains unexplored. However, deploying HR without understanding its potential effects on proprioception accuracy may pose risks to users in real-life situations. To investigate this, we conducted an experiment with 22 participants, studying the influence of prolonged exposure to unnoticeable HR offsets on proprioceptive accuracy during hand-reaching in VR. Our results show that proprioceptive accuracy declines significantly after prolonged exposure to redirected hand interactions. However, short-time exposure to unaltered hand interactions can – yet only partially – restore normal levels. Thus, we advocate being aware of potential risks arising from prolonged exposure to visual-proprioceptive offsets to ensure users’ safety.2025MFMartin Feick et al.Haptic WearablesHand Gesture RecognitionUIST
Will Health Experts Adopt a Clinical Decision Support System for Game-Based Digital Biomarkers? Investigating the Impact of Different Explanations on Perceived Ease-of-Use, Perceived Usefulness, and TrustThis paper explores the adoption of a clinical decision support system (cDSS) utilizing game-based digital biomarkers for diagnosing mild cognitive impairment (MCI). Specifically, it investigates how different explanation methods, with a focus on data-centric explanations, impact perceived ease-of-use, perceived usefulness, and trust among healthcare professionals (HCPs). Through a qualitative study with 12 HCPs, we assess their interactions with an explainable AI (XAI)-enriched cDSS. The findings indicate that HCPs are open to adopting XAI-enriched cDSS to communicate the outcomes of game-based digital biomarkers. HCPs preferred to receive key diagnostic information in an easily digestible format. Both local explanations of intra-personal evolutionary data and global overview of normative data were found to be valuable for interpreting digital biomarkers. HCPs tended to trust the machine learning algorithms as a black box, but they considered the dataset used for training the model and the outcome prediction to be crucial. Therefore, presenting the uncertainty alongside the prediction was deemed important. These insights underscore the importance of designing cDSS tools that foster trust through clear, actionable explanations, paving the way for improved decision-making in clinical contexts.2025CYChen Yu et al.Explainable AI (XAI)Mental Health Apps & Online Support CommunitiesIUI
"Is This Seat Accessible for Me?": An Autoethnography of a Person With a Mobility Disability Using Interactive Seat Plans for Public EventsSpectating sports matches or concerts is a popular activity, but these public live events have yet to become more accessible to people with disabilities. Inspecting the corresponding interactive seat plan before purchasing tickets online can be necessary to avoid or prepare for barriers at these venues. Unfortunately, these representations often lack valuable accessibility information. To explore how this can affect the disabled community, we leverage autoethnography to provide an in-depth introspective account through the lens of a person with a mobility disability. We apply Thematic Analysis to synthesise field notes from his research diary. The crafted themes showcase the lacking accessibility support in seat plans and illustrate the first author’s adaptation strategies to facilitate accessible experiences. We further contextualise his social relationships as a key factor throughout this process. Grounded in these results, we reflect on the provision of accessibility information, the categorisation of seats, and interdependent relationships within and through these systems.2025LSLukas Strobel et al.Karlsruhe Institute of TechnologyMotor Impairment Assistive Input TechnologiesUniversal & Inclusive DesignCHI
Scrolling in the Deep: Analysing Contextual Influences on Intervention Effectiveness during Infinite Scrolling on Social MediaInfinite scrolling on social media platforms is designed to encourage prolonged engagement, leading users to spend more time than desired, which can provoke negative emotions. Interventions to mitigate infinite scrolling have shown initial success, yet users become desensitized due to the lack of contextual relevance. Understanding how contextual factors influence intervention effectiveness remains underexplored. We conducted a 7-day user study (N=72) investigating how these contextual factors affect users' reactance and responsiveness to interventions during infinite scrolling. Our study revealed an interplay, with contextual factors such as being at home, sleepiness, and valence playing significant roles in the intervention's effectiveness. Low valence coupled with being at home slows down the responsiveness to interventions, and sleepiness lowers reactance towards interventions, increasing user acceptance of the intervention. Overall, our work contributes to a deeper understanding of user responses toward interventions and paves the way for developing more effective interventions during infinite scrolling.2025LMLuca-Maxim Meinhardt et al.Institute of Media Informatics, Ulm UniversityNotification & Interruption ManagementCHI
Exploring Flow in Real-World Knowledge Work Using Discrete cEEGrid SensorsFlow, a state of deep task engagement, is associated with optimal experience and well-being, making its detection a prolific HCI research focus. While physiological sensors show promise for flow detection, most studies are lab-based. Furthermore, brain sensing during natural work remains unexplored due to the intrusive nature of traditional EEG setups. This study addresses this gap by using wearable, around-the-ear EEG sensors to observe flow during natural knowledge work, measuring EEG throughout an entire day. In a semi-controlled field experiment, participants engaged in academic writing or programming, with their natural flow experiences compared to those from a classic lab paradigm. Our results show that natural work tasks elicit more intense flow than artificial tasks, albeit with smaller experience contrasts. EEG results show a well-known quadratic relationship between theta power and flow across tasks, and a novel quadratic relationship between beta asymmetry and flow during complex, real-world tasks.2025MKMichael Thomas Knierim et al.Karlsruhe Institute of Technology (KIT), Institute of Information Systems and Marketing (IISM)Brain-Computer Interface (BCI) & NeurofeedbackKnowledge Worker Tools & WorkflowsCHI
It's a Match - Enhancing the Fit between Users and Phishing Training through PersonalisationEffective training is essential for enhancing users' ability to detect phishing attempts. Personalised training offers huge potential to more closely align training content with individuals' needs and skill levels. In an online study, we assigned N=342 participants to personalised training or a random training variant to compare their effectiveness. The personalisation was based on a phishing proficiency score calculated from factors such as detection ability, knowledge, and security attitude. After training, the participants demonstrated greater proficiency, with an increased ability to detect phishing emails and higher security attitudes. These effects were most pronounced in the personalised condition, demonstrating the potential of personalisation to improve training outcomes. Overall, personalised training levelled the playing field, efficiently bringing all groups, regardless of their initial proficiency, to a comparable and desired post-training phishing proficiency level. Finally, we derived recommendations for designing personalised phishing training content and assigning users to suitable training programmes.2025LSLorin Schöni et al.ETH Zurich, Security, Privacy & SocietyExplainable AI (XAI)Cybersecurity Training & AwarenessCHI
Work Hard, Play Harder: Intense Games Enable Recovery from High Mental Workload TasksPlaying games has been shown to be an effective method of post-work recovery. Previous research has shown that gameplay with high cognitive involvement is effective for recovery. This finding conflicts with models of mental workload (MWL), which suggest that people feel best when cycling between high and low MWL. To unpack the relationship between recovery and mental workload, we designed a lab experiment where 40 participants experienced different combinations of high and low MWL while undertaking both work tasks and recovery gameplay, and we collected both self-report and physiological (fNIRS) data. Results showed that high and low MWL games created different impacts on recovery, depending on the MWL of the prior work task. While fNIRS measurements of MWL varied as expected during work tasks, experience of MWL when playing games was not evident in the prefrontal cortex. We conclude by discussing the relationship between mental workload and theories of recovery.2025LZLinqi Zhao et al.University of Nottingham, School of Computer ScienceGame UX & Player BehaviorSerious & Functional GamesCHI