Human-GDPR Interaction: Practical Experiences of Accessing Personal DataIn our data-centric world, most services rely on collecting and using personal data. The EU’s General Data Protection Regulation (GDPR) aims to enhance individuals’ control over their data, but its practical impact is not well understood. We present a 10-participant study, where each participant filed 4-5 data access requests. Through interviews accompanying these requests and discussions scrutinising returned data, it appears that GDPR falls short of its goals due to non-compliance and low-quality responses. Participants found their hopes to understand providers’ data practices or harness their own data unmet. This causes increased distrust without any subjective improvement in power, although more transparent providers do earn greater trust. We propose designing more effective, data-inclusive and open policies and data access systems to improve both customer relations and individual agency, and also that wider public use of GDPR rights could help with delivering accountability and motivating providers to improve data practices.2022ABAlex Bowyer et al.Newcastle UniversityPrivacy by Design & User ControlPrivacy Perception & Decision-MakingCHI
Investigating the Tradeoffs of Everyday Text-Entry Collection MethodsTyping on mobile devices is a common and complex task. The act of typing itself thereby encodes rich information, such as the typing method, the context it is performed in, and individual traits of the person typing. Researchers are increasingly using a selection or combination of experience sampling and passive sensing methods in real-world settings to examine typing behaviours. However, there is limited understanding of the effects these methods have on measures of input speed, typing behaviours, compliance, perceived trust and privacy. In this paper, we investigate the tradeoffs of everyday data collection methods. We contribute empirical results from a four-week field study (N=26). Here, participants contributed by transcribing, composing, passively having sentences analyzed and reflecting on their contributions. We present a tradeoff analysis of these data collection methods, discuss their impact on text-entry applications, and contribute a flexible research platform for in the wild text-entry studies.2022ARAndré Rodrigues et al.Universidade de Lisboa360° Video & Panoramic ContentComputational Methods in HCICHI
Tensions and Mitigations: Understanding Concerns and Values around Smartphone Data Collection for Public Health EmergenciesSmartphones increasingly serve as the source for, or to aggregate, a considerable amount of data that can be relevant in public health emergencies. Hence the sharing and utilisation of mobile health data, for example to help control the spread of communicable diseases, has become a relevant issue, with the COVID-19 pandemic adding a sudden urgency mirrored in debates around contact tracing apps. Building on exploratory work that indicated user perceptions and values around consent, and the notion that smartphones and mobile health data can be perceived as elements of self-embodiment, we present an online study comparing three scenarios of representative diseases undertaken during the first wave lockdown in the UK. Using a mixed-methods analysis of responses from 86 participants, we identify tensions and mitigations in user values and from those present the description of four characteristic user-groups that can inform considerations for design and development activities in this space.2021CWColin Watson et al.Data Work Across Contexts and DisciplinesCSCW
Fragments of the Past: Configuring Peer Support with Perpetrators of Domestic ViolenceThere is growing evidence that digital peer-support networks can have a positive influence on behaviour change and wellbeing outcomes for people who harm themselves and others. However, making and sustaining such networks are subject to ethical and pragmatic challenges, particularly for perpetrators of domestic violence who pose unique risks when brought together. In this work, we report on a ten-month study where we worked with six support workers and eighteen perpetrators in the design and deployment of Fragments of the Past; a socio-material system that connects audio messages with tangible artefacts. We share how crafting digitally-augmented artefacts - ‘fragments’ - of experiences of desisting from violence can translate messages for motivation and rapport between peers, without subjecting the process to risks inherent with direct interpersonal communication. These insights provide the basis for practical considerations for future network design with challenging populations.2021RBRosanna Bellini et al.Newcastle UniversityEmpowerment of Marginalized GroupsParticipatory DesignCHI
Content Creation in Later Life: Reconsidering Older Adults' Digital Participation and InclusionIn increasingly digitalised societies, government initiatives to ensure that public services remain accessible for everyone typically focus on the digital inclusion of older adults. However, by solely viewing older adults as passive recipients or consumers of services, digital inclusion strategies under-emphasise the concept of digital participation. Highlighting the importance of older adults as active contributors in a digital society, we investigated the potential of content creation to increase older adults’ digital skills whilst also strengthening their digital participation. Through a workshop and interviews involving three different groups of older content producers, we show that content creation can stimulate older adults’ digital participation. We report on challenges faced by the content creators, including time constraints, lack of professional support and the preference to create content collaboratively. We propose that by facilitating collaborative content creation activities, local communities can better support older adults’ digital participation and facilitate inclusion across different life domains.2020ARArlind Reuter et al.Family, Home, and Aging with TechnologyCSCW
Breaking The Experience: Effects of Questionnaires in VR User StudiesQuestionnaires are among the most common research tools in virtual reality (VR) evaluations and user studies. However, transitioning from virtual worlds to the physical world to respond to VR experience questionnaires can potentially lead to systematic biases. Administering questionnaires in VR (inVRQs) is becoming more common in contemporary research. This is based on the intuitive notion that inVRQs may ease participation, reduce the Break in Presence (BIP) and avoid biases. In this paper, we perform a systematic investigation into the effects of interrupting the VR experience through questionnaires using physiological data as a continuous and objective measure of presence. In a user study (n=50), we evaluated question-asking procedures using a VR shooter with two different levels of immersion. The users rated their player experience with a questionnaire either inside or outside of VR. Our results indicate a reduced BIP for the employed inVRQ without affecting the self-reported player experience.2020SPSusanne Putze et al.University of BremenImmersion & Presence ResearchCHI
Choice-Point: Fostering Awareness and Choice with Perpetrators in Domestic Violence InterventionsLearning about alternatives to violence is an essential part of change work with domestic violence perpetrators. This is complex work, seeking to tackle a sensitive issue by involving the development of deep, embodied learning for perpetrators who may lack perspective on their behaviour. Interactive storytelling has been providing users with the opportunity to explore speculative scenarios in a controlled environment. We discuss the design of Choice-Point: a web-based application that allows perpetrators adopt the role of different fictional characters in an abusive scenario for conveying the essential skill of perspective-taking. We evaluated Choice-Point through trials with three groups of perpetrators, a support group of victim-survivors and an expert critique from support workers. We discuss challenges in using such technologies - such as our system – for engagement; the value of perpetrator agency in supporting non-violent behaviours, and the potential to positively shape perpetrators' journeys to non-violence within social care settings.2020RBRosanna Bellini et al.Newcastle UniversityTechnology Ethics & Critical HCIParticipatory DesignCHI
Mechanisms of Moral Responsibility: Rethinking Technologies for Domestic Violence Prevention WorkThis paper provides a critical examination of how digital systems within a charitable organisation in the North of England are being used to both support and challenge male perpetrators of domestic violence. While there exists a range of digital tools to support the victim-survivors of domestic violence, no tools are available to challenge the abusive and harmful behaviours of perpetrators. Through this work, we uncovered the compelling moral responsibilities intrinsic within interactions with technological systems between perpetrators and support workers. As such, we highlight four spaces of negotiation concerning a person's responsibility in changing their abusive behaviour, which we have coined as mechanisms to represent their fundamental and interconnected nature. These mechanisms include self-awareness, acknowledging the extent of harms, providing peer support and respecting authorities. These insights are the basis for offering some practical considerations for HCI scholars, policymakers and intervention designers in their work with perpetrators of violence.2020RBRosanna Bellini et al.Newcastle UniversityUniversal & Inclusive DesignEmpowerment of Marginalized GroupsTechnology Ethics & Critical HCICHI
Bot or not? User Perceptions of Player Substitution with Deep Player Behavior ModelsMany online games suffer when players drop off due to lost connections or quitting prematurely, which leads to match terminations or game-play imbalances. While rule-based outcome evaluations or substitutions with bots are frequently used to mitigate such disruptions, these techniques are often perceived as unsatisfactory. Deep learning methods have successfully been used in deep player behavior modelling (DPBM) to produce non-player characters or bots which show more complex behavior patterns than those modelled using traditional AI techniques. Motivated by these findings, we present an investigation of the player-perceived awareness, believability and representativeness, when substituting disconnected players with DPBM agents in an online-multiplayer action game. Both quantitative and qualitative outcomes indicate that DPBM agent substitutes perform similarly to human players and that players were unable to detect substitutions. Notably, players were in fact able to detect substitution with agents driven by more traditional heuristics.2020JPJohannes Pfau et al.University of BremenGame UX & Player BehaviorSerious & Functional GamesCHI
Examining Design Choices of Questionnaires in VR User StudiesQuestionnaires are among the most common research tools in virtual reality (VR) user studies. Transitioning from virtuality to reality for giving self-reports on VR experiences can lead to systematic biases. VR allows to embed questionnaires into the virtual environment which may ease participation and avoid biases. To provide a cohesive picture of methods and design choices for questionnaires in VR (inVRQ), we discuss 15 inVRQ studies from the literature and present a survey with 67 VR experts from academia and industry. Based on the outcomes, we conducted two user studies in which we tested different presentation and interaction methods of inVRQs and evaluated the usability and practicality of our design. We observed comparable completion times between inVRQs and questionnaires outside VR (nonVRQs) with higher enjoyment but lower usability for \inVRQs. These findings advocate the application of inVRQs and provide an overview of methods and considerations that lay the groundwork for inVRQ design.2020DADmitry Alexandrovsky et al.University of BremenImmersion & Presence ResearchUser Research Methods (Interviews, Surveys, Observation)Prototyping & User TestingCHI
Enemy Within: Long-term Motivation Effects of Deep Player Behavior Models for Dynamic Difficulty AdjustmentBalancing games and producing content that remains interesting and challenging is a main cost factor in the design and maintenance of games. Dynamic difficulty adjustments (DDA) can successfully tune challenge levels to player abilities, but when implemented with classic heuristic parameter tuning (HPT) often turns out to be very noticeable, e.g. as "rubber-banding". Deep learning techniques can be employed for deep player behavior modeling (DPBM), enabling more complex adaptivity, but effects over frequent and longer-lasting game engagements, as well as how it compares to HPT has not been empirically investigated. We present a situated study of the effects of DDA via DPBM as compared to HPT on intrinsic motivation, perceived challenge and player motivation in a real-world MMORPG. The results indicate that DPBM can lead to significant improvements in intrinsic motivation and players prefer game experience episodes featuring DPBM over experience episodes with classic difficulty management.2020JPJohannes Pfau et al.University of BremenGame UX & Player BehaviorSerious & Functional GamesGamification DesignCHI