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Eliciting Meaningful Collaboration Metrics: Design Implications for Self-Tracking Technologies at Work

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Human-Computer Interaction – INTERACT 2023 (INTERACT 2023)

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Abstract

As the workplace collaboration software market is booming, there is an opportunity to design tools to support reflection and self-regulation of collaboration practices. Building on approaches from personal informatics (PI), we aim to understand and promote the use of data to enable employees to explore their work practices, specifically collaboration. Focused on the preparation stage of PI (deciding to track and tools selection), we invited office workers (N=15, knowledge workers in academia) to identify meaningful aspects of their collaboration experience and report them in a logbook for two weeks. We then conducted semi-structured interviews with participants to identify and reflect on metrics related to collaboration experience. We contribute new insights into employees’ motivations and envisioned metrics reflecting their collaboration, including the personal, social, and organizational considerations for collecting and sharing this data. We derive design implications for self-tracking technologies for collaboration.

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Acknowledgements

This research has been supported by the Luxembourg National Research Fund (FNR) IPBG2020/IS/14839977/C21.

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Authors and Affiliations

  1. University of Luxembourg, 2, Avenue de l’Université, 4366, Esch-sur-Alzette, Luxembourg

    Alina Lushnikova, Kerstin Bongard-Blanchy, Vincent Koenig & Carine Lallemand

  2. Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands

    Carine Lallemand

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  1. Alina Lushnikova
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  2. Kerstin Bongard-Blanchy
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  3. Vincent Koenig
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  4. Carine Lallemand
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Correspondence to Alina Lushnikova .

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Editors and Affiliations

  1. University of West London, London, UK

    José Abdelnour Nocera

  2. Reykjavik University, Reykjavik, Iceland

    Marta Kristín Lárusdóttir

  3. University of York, York, UK

    Helen Petrie

  4. University of Bari Aldo Moro, Bari, Italy

    Antonio Piccinno

  5. Université Côte d’Azur, Sophia Antipolis Cedex, France

    Marco Winckler

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Lushnikova, A., Bongard-Blanchy, K., Koenig, V., Lallemand, C. (2023). Eliciting Meaningful Collaboration Metrics: Design Implications for Self-Tracking Technologies at Work. In: Abdelnour Nocera, J., Kristín Lárusdóttir, M., Petrie, H., Piccinno, A., Winckler, M. (eds) Human-Computer Interaction – INTERACT 2023. INTERACT 2023. Lecture Notes in Computer Science, vol 14144. Springer, Cham. https://doi.org/10.1007/978-3-031-42286-7_36

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