Our team is very proud that our paper for ACM CSCW 2018 “Domino: A Descriptive Framework for Hybrid Collaboration and Coupling Styles in Partially Distributed Teams” has received a Best Paper Award!

The starting point of our work was our observation that partially-distributed teams (i.e. teams with co-located and remote members) use computing technologies in unexpected ways to work together. We refer to these practices as “hybrid collaboration”.

Our simulated setting of hybrid collaboration during our user study.

Hybrid collaboration is different from traditional concepts or models of CSCW because there are many transitions between co-located & remote collaboration and synchronous & asynchronous work. This becomes possible, because the teams use video and audio channels for creating awareness, simultaneously use many different devices (e.g. tablets, smartphones, large interactive whiteboards), and work across different applications and digital workspaces.

To better describe and understand hybrid collaboration, we simulated a collaborative activity at three different locations with a total of four team members in our lab. Participants used different devices for collaboration, including tablets, a 84″ Microsoft Surface Hub, and desktop PCs. We recorded and analyzed their behavior and developed a descriptive framework to describe team behavior and working styles.

Our resulting descriptive framework allows researchers to view hybrid collaboration through a new analytical lens, apply new analytical tools, and also derive implications for the design of future collaborative systems.

Please have a look at the pre-print version of the paper here.

Neumayr, T.; Jetter, H.-C.; Augstein, M.; Friedl, J.; Luger, T.: Domino: A Descriptive Framework for Hybrid Collaboration and Coupling Styles in Partially Distributed Teams. Proceedings of the ACM on Human-Computer Interaction (PACM), Vol 2, CSCW, Article 128, November 2018.

This work became possible through the support of the SCOLA project by the government of Upper Austria. This research was also supported by the Austrian Research Promotion Agency (FFG) as part of the COIN capacity building project “USIVIS – User Centered Interactive Visualization for Big Data”.

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