While at Stanford, Michael Bernstein and I, with the help of many great undergrads, designed an experiment to study the consistency of team fracture, a notion we defined as a loss of team viability so severe that the team no longer wants to work together CSCW’19.

We asked, was a problematic team always doomed to frustration, or could it have ended another way?

To study this, we introduce an online experiment that reconvenes the same team repeatedly, without members realizing that they have worked together before, enabling us to temporarily erase previous team dynamics. We found that reconvened teams are strikingly polarized by task in the consistency of their fracture outcomes — on a creative task, teams might as well have been a completely different set of people: the same teams changed their fracture outcomes at a random chance rate, on the other hand on a cognitive conflict and on an intellective task, the team instead replayed the same dynamics without realizing it, rarely changing their fracture outcomes. Our results indicate that, for some tasks, team fracture can be strongly influenced by interactions in the first moments of a team’s collaboration, and that interventions targeting these initial moments may be critical to scaffolding long-lasting teams.

In follow up work, we studied the predictability of team fracture CSCW’21, using a range of human rated and automatically generated features. We found that automatically generated features alone served as a strong predictor of team fracture. We made the underlying system available at viability.stanford.edu.