Team Science Practices

Overview

In this module, we’ll dive into some of the literature underlying our recommended team science practices (the science of team science). We’ll also explore some of the more common types of conflicts that arise in synthesis work and ways to anticipate, prevent (when possible), and resolve those conflicts.

Learning Objectives

After completing this module you will be able to:

  • Interpret and enact current best practices in team science
  • Identify different interaction styles and the effect they have on group dynamics
  • Identify benefits (and potential costs of) diverse teams
  • Describe ways to mitigate costs of diverse teams
  • Explain methods for improving the experience of virtual participants on hybrid teams

Preparation

Each project group should:

  • Plan on providing a 3-5 minute project summary and update on recent progress and any questions/issues that are arising
  • Finish their internal ground rules (if not already complete)

Networking Session

We’ll begin this session’s discussion with a conversation among participants in a recent synthesis group that tackled a particularly broad disciplinary stretch. The Synthesizing population and community synchrony to understand drivers of ecological stability across LTER sites brought together mathematicians, modelers, and empiricists to apply novel analytical strategies to understanding the impact of population fluctuations.

Panelists will briefly introduce themselves and their experience with the synthesis group, which encountered a variety of challenges in their work. Ultimately, they produced several effective and well-received papers, but they had to introduce some innovations in working group approach to get there.

Science of Team Science

Research in management, organizational behavior, and psychology has long focused on the performance of teams–often in military, healthcare and industrial contexts. While many aspects of this work are also relevant to scientific teams, there are some key differences having to do with differences in context, leadership, and incentives. In the early 2000’s–as collaboration in science increased–the need for empirical research into the workings of science teams became apparent. The field of “science of team science” or SiTS was launched in 2006 with a conference at the National Institutes of Health (Stokols et al. 2008).

A National Academies study on the Science of Team Science (NRC 2015) assembled the existing evidence base and launched a flurry of research into how team composition, coordination, support, and organizational context could improve outcomes for science teams. A new National Academies study on Research and Application in Team Science is currently in progress. Our goal here is not to review the whole field, but to provide a framework for thinking about the team functioning and process and to identify some key team science practices that are supported by both research and practical experience.

Teams have a Predictable Trajectory

Creating a team is not just a matter of putting a bunch of people in a room together. Social scientists have identified consistent patterns in the evolution of teams (Tuckman 1965, Tuckman and Jenson 1977). Knowing that this is a process nearly every team experiences may make it (at least somewhat) more comfortable.

graphic, laying out the 5 phases: forming, storming, norming, performing, and adjourning, with accompanying fluctuations in team performance

Teams that are assembled from across organizations must agree to adopt a common set of norms and processes in order to progress from storming to performing. This can feel like a detour from the science, but a modest early investment in developing shared practices pays off in the long run.

Instrumental Benefits of Diverse Teams

Graph showing novelty peaks at a team size of about 6 authors (examining only authors from a single private university). From: Lee et al. 2014

There is pretty good evidence that collaborative teams produce research that is more novel and has higher impact than work produced by individuals or smaller more homogeneous groups (Lee at al. 2015, Hong and Page 2024). Woolley et al (2010) found evidence for a “collective intelligence” in teams, which is not strongly correlated with the average or maximum individual intelligence of group members but is correlated with the average social sensitivity of group members, the equality in distribution of conversational turn-taking, and the proportion of females in the group.

Similarly, in a study of 6.6 million medical research papers, Yang et al. found that mixed gender teams consistently produced more novel and more impactful products. In another bibliographic analysis Abbasi and Jaafari (2013) found that inter-institute and inter-university collaborations resulted in higher-impact publications. Interestingly, the result was much weaker for international collaborations.

Graph showing that mixed-gender teams are more likely to produce novel papers than same-gender teams at all team sizes
Mixed-gender teams are more likely to produce novel papers than same-gender teams at all team sizes. Mixed-gender teams are also more likely to publish an upper-tail paper than same-gender teams by as much as 14.6%, depending on team sizes.

Colored background behind the quote 'If you want to go fast, go alone; if you want to go far, go together'

It seems reasonable to expect that the effects of cultural and economic diversity on teams would be similar to that of gender diversity, but those factors remain harder to parse at this scale. In any case, the bump in creativity or publishing impact is only a happy side effect of assembling a diverse team. The real reason to do so is that it allows us to tackle bigger questions, makes our findings more relevant, our science more fun, and our world more fair. What it does not do (at least in our experience) is make the process faster!

A More Nuanced View Emerges

The paradox of team science is that the very factors that slow progress may be exactly the factors that generate new insight – Milliken and Martins’ (1996) double-edged sword. The pressing question becomes not: “Does diversity improve team performance?” but rather: “How and when does diversity improve team performance?”

What Mechanisms are Responsible for the Diversity Effect?

Information Elaboration

The categorization-elaboration model (CEM, van Knippenberg et al. 2004) proposed that information elaboration—-that is, the exchange, discussion, and integration of task-relevant information and perspectives, was responsible for many of the benefits attributed to diverse groups. But later researchers found there were a few necessary conditions for cognitive elaboration to take place and for groups to reap the benefits. Only when team members brought a learning goal orientation to their work and when they remained open to revising their original ideas (Nederveen Pieterse 2013) did diversity improve team performance.

Avoiding ‘groupthink’

We are all familiar with the “we’ve always done it this way” effect that can happen when a group of people have been working together for a while. By introducing people from new fields, laboratories, or cultures, that complacent thinking is disrupted. Often, the very act of justifying why we do something the way we do can invite a rethinking and improvement.

Metacognition

Metacognition, or “thinking about thinking” requires individuals to reflect and articulate their process for achieving new knowledge. What information goes in? Is information missing? How should it be analyzed and interpreted? Are those conclusions justified?

Enhanced group scanning ability and consideration of alternative solutions

A science team may include members from different research disciplines, sectors, geographies or cultures. Along each of those axes, team members will have different personal networks and be more (or less) familiar with different literatures, models, communities, tools, and solutions. Collectively, the group has a much broader range of information to draw on…but only if group members feel empowered to contribute.

Better task completion and more efficient use of resources

“Many hands make light work” the saying goes. Think of a meta-analysis where 10 group members can each read 30 papers instead of 1 individual reading 300 papers. Dividing the workload can speed up the process, but only if there is an efficient way to manage dividing the work and then bringing the results back together again. Similarly, relying on a few skilled coders can be much more efficient than each individual writing their own code, but unless the group has a mechanism for getting broad input on key decisions, they will lose the value created by bringing together a larger group.

Activity: Draft Your Team’s Practices

In your project group, come up with one practice that you could include in your group practice guidelines to support each of the above mechanisms

We will then reconvene as a class and each project group will describe one of their practices and how they think it will help.

Conditions and Practices that Support Team Functioning

In order for the above mechanisms to operate, teams need to cultivate conditions that encourage all members to contribute at the times and in the ways that they are most skilled and effective. Explore the tabs below for some of these conditions.

Cultivate a learning goal orientation rather than a product goal orientation. Expect to learn from one another and adapt your expectations and plans (Nederveen et al. 2013)

Remain open to revising assumptions and world views. When divergent positions are met only with resistance, groupthink gains the upper hand

Cognitive trust is the rational belief that group members can and will deliver on their portion of the work. When it isn’t present, group members tend to pull back on their own contributions. Good coordination supports cognitive trust by providing clarity and accountability about who agreed to do what work and whether they delivered. It ensures that contributions can be appropriately credited and that work isn’t unnecessarily duplicated. Effective coordination and facilitation make space for all group members to engage.

  • Fast and slow processors can be accommodated by making space for written as well as verbal contributions and allowing “thinking time” before expecting a response.
  • Visual, auditory and kinesthetic learners take in information (and are more or less fluent) in different formats. Try to provide key information (and allow input) in more than one format.
  • Those with caregiving responsibilities may have unpredictable availability and shorter periods of concentrated effort. A task management system (such as GitHub Projects or Trello) that breaks down tasks into manageable chunks and provides necessary contexts can help them contribute without as much task-switching cost.
  • Strategies for managing different geographies include virtual meetings, pulsed contributing times, and asynchronous editing of shared documents.

Affective trust is the belief (usually grounded in common experience) that group members have your best interests in mind. Some strategies for building it include:

  • Spend social time together - meals, activities when in-person, but also, don’t skimp on icebreakers and check-ins when virtual
  • Pay attention to mutual respect and speaking time. Explicitly acknowledge and credit new ideas as they come up.
  • Be willing to look foolish. Ask the “dumb” questions that surface unquestioned assumptions. When some (leaders especially) make themselves vulnerable, it provides safety for others to do so.
  • Consider assigning a vibes-keeper to track when the group becomes impatient, offended, or disengaged.
  • Spend time early to talk through various perspectives on the question that may be present in the group.
  • Attend to conflicts as they arise.

All Contribute Some; None Contribute All

Graphic showing how 'team communication', 'collaborative problem-solving' and 'managing team research' intersect and how those intersections benefit either team bonding or team leadership
Overlapping and intersecting competencies across the domains (from Lotrecchiano et al. 2021). Colors define the primary domain for each competency.

Additional Resources

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