5 research outputs found

    Proposing design recommendations for an intelligent recommender system logging stress

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    Abstract The connection between stress and smartphone usage behavior has been investigated extensively. While the prediction results using machine learning are encouraging, the challenge of how to cope with data loss remains. Addressing this problem, we propose an Intelligent Recommender System for logging stress based on adding a subjective user data-based validation to predictions made by intelligent algorithms. In a user study involving 731 daily stress self-reports from 30 participants we found discrepancies between subjective and smartphone usage data, i.e. battery, call information, or network usage. Despite the good prediction accuracy of 65% using a Random Forest classifier, combining both information would be beneficial for avoiding data and improving prediction accuracy. For realizing such a system (i.e., a mobile application), we propose three design recommendations, based on the capabilities of frequently used machine learning classifiers, enabling users to annotate their daily stress levels with a predict-and-validate methodology

    Understanding Grassroots Sports Gamification in the Wild

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    While gamification is an often used tool in building interactive experiences for sports, little work has addressed systems designed by users for users and deeply embedded in the social setting of physical exercise. Consequently, a better understanding of sports gamification in the wild is needed to build systems that reflect the users' pre-existing social context. This paper presents a qualitative study of a gamification system, the Boar Board, designed by a sports coach to support users participating in regular exercises. Through surveys, interviews and observations over eight months, we built an understanding of the user adoption of the system and how the Boar Board supported the goals of the group. Based on this, we endeavour to understand the social aspects of the system, including trust, and posit a number of design considerations for future inquiry into gamification systems for sports

    Understanding Grassroots Sports Gamification in the Wild

    No full text
    While gamification is an often used tool in building interactive experiences for sports, little work has addressed systems designed by users for users and deeply embedded in the social setting of physical exercise. Consequently, a better understanding of sports gamification in the wild is needed to build systems that reflect the users' pre-existing social context. This paper presents a qualitative study of a gamification system, the Boar Board, designed by a sports coach to support users participating in regular exercises. Through surveys, interviews and observations over eight months, we built an understanding of the user adoption of the system and how the Boar Board supported the goals of the group. Based on this, we endeavour to understand the social aspects of the system, including trust, and posit a number of design considerations for future inquiry into gamification systems for sports

    AVotar:exploring personalized avatars for mobile interaction with public displays

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    Abstract Engaging users with public displays has been a major challenge in public display research. Interactive displays often suffer from being ignored by potential users. Research showed that user representations are a valid way to partially address this challenge, e.g., by attracting attention, conveying interactivity, and serving as entry points to gestures and touch interaction. We believe that user representations, particularly personalized avatars, could further increase the attractiveness of public displays, if carefully designed. In this work, we provide first insights on how such avatars can be designed and which properties are important for users. In particular, we present AVotar, a voting application for mobiles that lets users design avatars being utilized to represent them. In an user study we found that users appreciate high degrees of freedom in customization and focus on expressive facial features. Finally, we discuss the findings yielding useful implications for designers of future public display applications employing avatars
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