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Auflistung nach Autor:in "Shahu, Ambika"

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  • Konferenzbeitrag
    Beyond Screen Time: Exploring Smartwatch Interventions for Digital Well-Being
    (Proceedings of Mensch und Computer 2024, 2024) Shahu, Ambika; Pechstein, Fabian; Michahelles, Florian
    In the digital age, technology permeates every aspect of our lives, offering connectivity but also posing risks to our well-being due to overuse. The concept of digital detox" has emerged as a response, with smartphone apps supporting this process, yet the potential of wearable tech like smartwatches is less explored. Our study develops and tests a smartwatch-integrated digital detox aid, aiming to seamlessly blend with tech ecosystems offering a holistic solution. A preliminary mixed method user study (n=6) over two weeks assessed its efficacy in cutting down phone usage and app screen time, alongside monitoring phone interactions and physiological data. Initial results showed a decrease in screen time, which diminished in the second week, suggesting participant resistance and the intervention’s perceived intrusiveness. Despite proving the concept’s feasibility, the need for more user-aligned intervention methods and technical enhancements is clear, pointing to areas for future improvement."
  • Konferenzbeitrag
    Enhancing the Supervision of Out-of-View Robots: A Study on Multimodal Feedback and Monitoring Screens
    (Mensch und Computer 2023 - Tagungsband, 2023) Kassem, Khaled; Shahu, Ambika; Tüchler, Christina; Wintersberger, Philipp; Michahelles, Florian
    Objective: investigating the effect of two support methods (multimodal feedback, monitoring screens, and a combination of both) on human dual-task performance, cognitive workload, and user experience when supervising an out-of-sight autonomous robot. Method: A 2x2 within-group user study was conducted in VR with 26 participants involving a cognitive-cognitive dual-task setting. Participants had to simultaneously solve math problems and supervise the robot. Different support methods were provided: multimodal feedback, a screen showing real-time robot activity, and a combination of both. Objective performance metrics and subjective feedback on cognitive load and user experience were collected using standard questionnaires. Data were statistically analyzed, and thematic analysis was performed on post-study debriefing interviews. Results: The support methods improved overall user experience and positively impacted robot collaboration performance while decreasing math task performance. Cognitive load was unaffected. Multimodal feedback with a monitoring screen was perceived as the most helpful. Conclusion: The results suggest that multimodal feedback can improve user experience and improve supervision, but may partially decrease primary task performance. The findings highlight the importance of examining the effect of support methods in specific situations, depending on task priority.