Convergent and divergent thinking

Stories of self, us, and now: A tool for navigating uncertainty

By Gemma Jiang, Alexis Niki, Darius Melvin and Sarah Hind.

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1. Gemma Jiang (biography)
2. Alexis Niki (biography)
3. Darius Melvin (biography)
4. Sarah Hind (biography)

In times of uncertainty, especially when the role of research, as well as research funding are under threat, how can research teams effectively respond? How can storytelling help?

We show how Marshall Ganz’s (2009) Stories of Self, Us, and Now framework can move groups from individual experiences of uncertainty (Self) to shared meaning (Us), and toward concrete action steps (Now).

Workshop Context

Leadership team members from a large transdisciplinary, cross-institutional research center, entering the fifth (final) year of their funding cycle, partnered with an external team science expert

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Decision support interventions

By Etiënne Rouwette and Alberto Franco

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1. Etiënne Rouwette (biography)
2. Alberto Franco (biography)

What are interventions to support team decision making? And how can interventions enable team decision making to become a rigorous, transparent and defensible process?

Interventions are procedures designed to improve a decision making process. Within the content of team decision making, an intervention is comprised of designed facilitated activities carried out in order to help a team achieve its goals. Team goals include generating a better and shared understanding of a situation of interest or concern, producing a recommendation on how to respond to the situation, or simply deciding what to do next regarding the situation.

Because team members are likely to have different views and goals regarding the situation, facilitation is central to an intervention. Specifically, facilitated activities are designed to encourage the active participation of team members in discussions, so that a mutual understanding within the team can be achieved. In addition, these activities also play a critical role in fostering the development of integrative solutions that create a sense of shared responsibility for their implementation.

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Stakeholder engagement primer: 8. Generating ideas and reaching agreement

By Gabriele Bammer

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What skills for generating ideas and reaching agreement should every researcher involved in stakeholder engagement seek to cultivate? What key methods and concepts should they be familiar with?

The focus in this blog post is on generating ideas and reaching agreement, as well as recognising the “groan zone” between these two phases in a group process. Researchers will have diverse attributes and not everyone will be well-placed to cultivate the skills described here. Having an understanding of the skills can help in choosing the researchers best placed to undertake the stakeholder engagement.

Generating ideas: Brainstorming

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A tool for transforming resistance to insights in decision-making

By Gemma Jiang

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Gemma Jiang (biography)

Do you encounter resistance from your team members, especially in regard to difficult decisions? How might decision-making processes be better facilitated to generate insights instead of resistance?

I describe a conceptual framework and an accompanying practical tool from Lewis Deep Democracy (2021) that can transform resistance to insights in decision-making processes.

The conceptual framework: Understanding how decision making generates resistance

It is important first to understand the consciousness of a team. If you think of a team’s consciousness as an iceberg, the ideas and opinions that are expressed are the conscious part above the waterline, while those that are not expressed are the unconscious part below the waterline.

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Enabling divergent and convergent thinking in cross-disciplinary graduate students

By Gemma Jiang

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Gemma Jiang (biography)

How can we enable graduate students to think in ways that open new possibilities, as well as to make good decisions based on diverse cross-disciplinary insights?

Here I describe how we have embedded 14 graduate students in a research team with nine faculty from four academic institutes, representing six disciplines (for simplicity only three disciplines – engineering, economics, and anthropology – are considered here). Our research addresses the circular economy. I have developed a three-step model (summarised in the figure below) to operationalize the “divergence-convergence diamond,” which is key to our teaching method.

The “divergence – convergence diamond” is widely used in design thinking. The divergent mode helps open new possibilities while the convergent mode helps evaluate what you have and make decisions. Both are important to cross-disciplinary collaboration.

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Collaboration: From groan zone to growth zone

By Carrie Kappel

Carrie Kappel (biography)

What is the groan zone in collaboration? What can you do when you reach that point?

As researchers and practitioners engaged in transdisciplinary problem-solving, we know the value of diverse perspectives. We also know how common it is for groups to run into challenges when trying to learn from diverse ideas and come to consensus on creative solutions.

This challenging, often uncomfortable space, is called the groan zone. The term comes from Sam Kaner’s diamond model of participation shown in the figure below. After an initial period of divergent thinking, where diverse ideas are introduced, groups have to organize that information, focus on what’s most important, and make decisions in order to move forward into the phase of convergent thinking.

Navigating that transition between divergent and convergent thinking is the realm in which creativity and innovation emerge, if we let them.

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Idea tree: A tool for brainstorming ideas in cross-disciplinary teams

By Dan Stokols, Maritza Salazar, Gary M. Olson, and Judith S. Olson

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1. Dan Stokols (biography)
2. Maritza Salazar (biography)
3. Gary M. Olson (biography)
4. Judith S. Olson (biography)

How can cross-disciplinary research teams increase their capacity for generating and integrating novel research ideas and conceptual frameworks?

A key challenge faced by research teams is harnessing the intellectual synergy that can occur when individuals from different disciplines join together to create novel ideas and conceptual frameworks. Studies of creativity suggest that atypical (and often serendipitous) combinations of dissimilar perspectives can spur novel insights and advances in knowledge. Yet, many cross-disciplinary teams fail to achieve intellectual synergy because they allot insufficient effort to generating new ideas. Here we describe a brainstorming tool that can be used to generate new ideas in cross-disciplinary teams.

The idea tree exercise

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What can interdisciplinary collaborations learn from the science of team science?

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Suzi Spitzer (biography)

By Suzi Spitzer

How can we improve interdisciplinary collaborations? There are many lessons to be learned from the Science of Team Science. The following ten lessons summarize many of the ideas that were shared at the International Science of Team Science Conference in Galveston, Texas, in May 2018.

1. Team up with the right people
On the most basic level, scientists working on teams should be willing to integrate their thoughts with their teammates’ ideas. Participants should also possess a variety of social skills, such as negotiation and social perceptiveness. The most successful teams also encompass a moderate degree of deep-level diversity (values, perspectives, cognitive styles) and include women in leadership roles.

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Harnessing analogies for creativity and problem solving

By Christian Schunn

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Christian Schunn (biography)

What is an analogy? How can analogies be used to work productively across disciplines in teams?

We know from the pioneering work of Kevin Dunbar (1995), in studying molecular biology labs, that analogies were a key factor in why multidisciplinary labs were much more successful than labs composed of many researchers from the same backgrounds. What is it about analogies that assists multi- and interdisciplinary work?

The advice that follows comes from a decade of research involving intensive analyses of hundreds of hours of interdisciplinary science and engineering teams, following the minute-by-minute processes of the teams, and using advanced statistical techniques to look for robust patterns in behavior over time and across teams. In general, our research has shown that creative teams generate twice as many ideas per unit time when they use analogies than when they do not.

So, what is an analogy?

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