1,121 research outputs found

    What's Your Problem with the Dog Internet?

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    In Contact:Pinching, Squeezing and Twisting for Mediated Social Touch

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    Does the Presence of Privacy Relevant Information Affect App Market Choice?

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    Worker-Centered Design: Expanding HCI Methods for Supporting Labor

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    HCI has long considered sites of workplace collaboration. From airline cockpits to distributed groupware systems, scholars emphasize the importance of supporting a multitude of tasks and creating technologies that integrate into collaborative work settings. More recent scholarship highlights a growing need to consider the concerns of workers within and beyond established workplace settings or roles of employment, from steelworkers whose jobs have been eliminated with post-industrial shifts in the economy to contractors performing the content moderation that shapes our social media experiences. This one-day workshop seeks to bring together a growing community of HCI scholars concerned with the labor upon which the future of work we envision relies. We will discuss existing methods for studying work that we find both productive and problematic, with the aim of understanding how we might better bridge current gaps in research, policy, and practice. Such conversations will focus on the challenges associated with taking a worker-oriented approach and outline concrete methods and strategies for conducting research on labor in changing industrial, political, and environmental contexts

    Predicting early user churn in a public digital weight loss intervention

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    Digital health interventions (DHIs) offer promising solutions to the rising global challenges of noncommunicable diseases by promoting behavior change, improving health outcomes, and reducing healthcare costs. However, high churn rates are a concern with DHIs, with many users disengaging before achieving desired outcomes. Churn prediction can help DHI providers identify and retain at-risk users, enhancing the efficacy of DHIs. We analyzed churn prediction models for a weight loss app using various machine learning algorithms on data from 1,283 users and 310,845 event logs. The best-performing model, a random forest model that only used daily login counts, achieved an F1 score of 0.87 on day 7 and identified an average of 93% of churned users during the week-long trial. Notably, higher-dimensional models performed better at low false positive rate thresholds. Our findings suggest that user churn can be forecasted using engagement data, aiding in timely personalized strategies and better health results

    Adopting an African Standpoint in HCI4D::A Provocation

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    While studies in HCI4D have been advanced by the shift of perspective from developmental studies to a range of other discourses, current analytical concepts for understanding the sociality of society in Africa have arguably led to some misinterpretations of the place of technology. This provocation suggests that an ‘African Standpoint’ based on a combination of various standpoint positionalities and the Wittgensteinian approach of Winch can offer conceptual and analytical sensitivities for articulating social relations, transnational engagements and the conceptualisation of technological innovation. This provides an approach for seeing and accounting for things as they are – right here, right there and right now – and not some idealised conception of an African reality

    PhysioKit: An Open-Source, Low-Cost Physiological Computing Toolkit for Single- and Multi-User Studies

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    The proliferation of physiological sensors opens new opportunities to explore interactions, conduct experiments and evaluate the user experience with continuous monitoring of bodily functions. Commercial devices, however, can be costly or limit access to raw waveform data, while low-cost sensors are efforts-intensive to setup. To address these challenges, we introduce PhysioKit, an open-source, low-cost physiological computing toolkit. PhysioKit provides a one-stop pipeline consisting of (i) a sensing and data acquisition layer that can be configured in a modular manner per research needs, and (ii) a software application layer that enables data acquisition, real-time visualization and machine learning (ML)-enabled signal quality assessment. This also supports basic visual biofeedback configurations and synchronized acquisition for co-located or remote multi-user settings. In a validation study with 16 participants, PhysioKit shows strong agreement with research-grade sensors on measuring heart rate and heart rate variability metrics data. Furthermore, we report usability survey results from 10 small-project teams (44 individual members in total) who used PhysioKit for 4–6 weeks, providing insights into its use cases and research benefits. Lastly, we discuss the extensibility and potential impact of the toolkit on the research community

    Get a Grip:Evaluating Grip Gestures for VR Input Using a Lightweight Pen

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    The use of Virtual Reality (VR) in applications such as data analysis, artistic creation, and clinical settings requires high precision input. However, the current design of handheld controllers, where wrist rotation is the primary input approach, does not exploit the human fingers' capability for dexterous movements for high precision pointing and selection. To address this issue, we investigated the characteristics and potential of using a pen as a VR input device. We conducted two studies. The first examined which pen grip allowed the largest range of motion---we found a tripod grip at the rear end of the shaft met this criterion. The second study investigated target selection via 'poking' and ray-casting, where we found the pen grip outperformed the traditional wrist-based input in both cases. Finally, we demonstrate potential applications enabled by VR pen input and grip postures
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