Pair research: matching people for collaboration, learning, and productivity

Authors:
Robert C. Miller;Haoqi Zhang;Eric Gilbert;Elizabeth Gerber
Affiliations:
Massachusetts Institute of Technology, Cambridge, MA, USA;Northwestern University, Evanston, IL, USA;Georgia Institute of Technology, Atlanta, GA, USA;Northwestern University, Evanston, IL, USA
Venue:
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
Year:
2014

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Abstract

To increase productivity, informal learning, and collaborations within and across research groups, we have been experimenting with a new kind of interaction that we call {em pair research}, in which members are paired up weekly to work together on each other's projects. In this paper, we present a system for making pairings and present results from two deployments. Results show that members used pair research in a wide variety of ways including pair programming, user testing, brainstorming, and data collection and analysis. Pair research helped members get things done and share their expertise with others.