Actor constellation role plays

By Alexandra Frangenheim.

alexandra-frangenheim
Alexandra Frangenheim (biography)

How can transdisciplinary researchers gain a better understanding of systemic and multi-causal problems, including recognising different thought styles, appreciating the complexity of intervening, and anticipating points of conflict?

Actor constellation is a role play for identifying the relevance of various actors involved in specific problems. It is useful for problem framing when a research team is formed, for example to plan empirical inquiries or to identify relevant actors for addressing research questions. It also enables researchers from different disciplines and practitioners to uncover hidden dynamics and possible systemic solutions to the problem of interest, and to unlock the potential of shifting perspectives to ultimately develop new narratives.

When research participants represent relevant actors in a role play, their implicit assumptions about relationships, structures, interaction and actors’ knowledge are made explicit.

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Decision support interventions

By Etiënne Rouwette and Alberto Franco

authors_etienne-rouwette_alberto-franco
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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Key systems thinking lessons from Donella Meadows

By Geoff Marlow

geoff-marlow
Geoff Marlow (biography)

The book “Thinking In Systems: A Primer” by Donella (Dana) Meadows (2008) offers a useful entry point into systems thinking via seven lessons.

Lesson 1: Systems are always more than the sum of their parts

Feedback loops are pivotal, as is looking beyond the players to the underlying rules of the game.

Meadows (p. 13) offers guidance as to “whether you are looking at a system or just a bunch of stuff:

  • Can you identify parts? . . . and
  • Do the parts affect each other? . . . and
  • Do the parts together produce an effect that is different from the effect of each part on its own? . . . and perhaps
  • Does the effect, the behavior over time, persist in a variety of circumstances?” 

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Interdisciplinary teamwork: Expert and non-expert at the same time

By Annemarie Horn and Eduardo Urias

authors_annemarie-horn_eduardo-urias
1. Annemarie Horn (biography)
2. Eduardo Urias (biography)

How do teams engage in interdisciplinary knowledge integration and how can they be supported in doing so? Why does simple sharing and questioning of knowledge not necessarily lead to interdisciplinary knowledge integration? And what does it mean to act as both an expert and a non-expert in interdisciplinary teamwork, and why is it hard?

In a five month course, we supervised a team of eight master students in the integration of insights and concepts from their individual, discipline-based projects into a joint work about circular economy. Based on our earlier research, described in our i2Insights contribution on four typical behaviours in interdisciplinary knowledge integration, we expected that if we helped the students to share their own knowledge and to engage with each other’s knowledge, that integration would emerge. We therefore had students prepare and give presentations about their individual projects, background, and conceptual underpinnings to share their knowledge.

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Improving facilitated modelling

By Vincent de Gooyert

vincent-de-gooyert
Vincent de Gooyert (biography)

Here I explore two outcomes of facilitated modelling – cognitive change and consensus forming – and ask: how can achieving those outcomes be improved?

But first, what is facilitated modelling?

Facilitated modelling is an approach where operational researchers act as facilitators to model an issue collaboratively with stakeholders, usually in a workshop. Operational research, also known as operations research, seeks to improve decision-making by developing and applying analytical methods.

Two central aims of facilitated modelling are to achieve cognitive change and to form consensus.

Cognitive change is the idea that participants of facilitated modelling workshops come in with a certain worldview, and that the intervention leads them to learn about the issue and accordingly change their minds.

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Externalizing implicit expectations and assumptions in transdisciplinary research

By Verena Radinger-Peer, Katharina Gugerell and Marianne Penker

authors_verena-radinger-peer_katharina-gugerell_marianne-penker
1. Verena Radinger-Peer (biography)
2. Katharina Gugerell (biography)
3. Marianne Penker (biography

How can implicit expectations and assumptions of team members in transdisciplinary research collaborations be identified?

We used Q-methodology as a tool to make diverse expectations and perceptions of transdisciplinary research collaborations tangible and thus negotiable.

Q-methodology is an established explorative, semi-quantitative method for investigating distinctive viewpoints of a given population based on inverted factor analysis. While we do not explain Q methodology here, it is increasingly used and we refer those who want to find out more to Watts and Stenner (2012).

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Clarifying incentives and expectations in research collaborations

By Alisa Zomer and Varja Lipovsek

authors_alisa-zomer_varja-lipovsek
1. Alisa Zomer (biography)
2. Varja Lipovsek (biography)

In which areas do research collaborations between academics and practitioners often run into trouble? What difficult questions can we ask ourselves and our partners at the outset of a research collaboration that can set us up for a successful partnership? How can we learn from past successful and failed aspects of research partnerships?

In our experience four areas where collaborations can have problems are:

  • Incentives and expectations
  • Timelines
  • Collaborative decision making and team buy-in
  • Learning and dissemination.

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Understanding diversity primer: 2. Mental models

By Gabriele Bammer

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What are mental models and why are they important? How do they affect how problems are framed, understood and responded to? How do they affect how well those contributing to the research work together?

Mental models are a person’s understanding of the world and how it works, and are unique to each person. They exist in a person’s mind as a set of small-scale simplified models about different aspects of reality that are functional but necessarily incomplete.

Mental models apply to all aspects of reality ranging from concrete objects such as a ‘chair;’ to abstract concepts such as ‘trust;’ to geographical locations such as ‘Sydney;’ to connections, interconnections and causal relationships; and to simple and complex situations.

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Boosting the transformative power of transdisciplinarity with quantum theory

By Cyrille Rigolot

cyrille-rigolot
Cyrille Rigolot (biography)

How can transdisciplinarity improve its ability to foster very deep, very fast and very large transformations toward sustainability?

Quantum theory might be a major source of insights in that direction. Although quantum theory is not new to transdisciplinarity, lately it has become much more accessible, practical, and potentially transformative on the ground.

Quantum theory for transdisciplinarity research

In the debates last century about the emerging transdisciplinary research field, quantum theory inspired theorist Basarab Nicolescu to develop three basic ‘axioms’, which he argues should be recognized at the core of transdisciplinarity research, namely:

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A heuristic framework for reflecting on joint problem framing

By BinBin Pearce and Olivier Ejderyan

authors_binbin-pearce_olivier-ejderyan
1. BinBin Pearce (biography)
2. Olivier Ejderyan (biography)

What is joint problem framing? What are the key issues that joint problem framing has to address? How can joint problem framing be improved?

What is joint problem framing?

A key aspect of tackling complex problems is effectively bringing together differing points of view. These points of view are what Craik (1943) refers to as “small-scale models” of the problem situation. These are mental models formed from each individual’s experiences, interests, knowledge and environment. These mental models then set the boundaries for what problem definitions and solutions are possible and relevant to consider.

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Why model?

By Steven Lade

Steven Lade
Steven Lade (biography)

What do you think about mathematical modelling of ‘wicked’ or complex problems? Formal modelling, such as mathematical modelling or computational modelling, is sometimes seen as reductionist, prescriptive and misleading. Whether it actually is depends on why and how modelling is used.

Here I explore four main reasons for modelling, drawing on the work of Brugnach et al. (2008):

  • Prediction
  • Understanding
  • Exploration
  • Communication.

I start with mental models – the informal representations of the world that we all use as we go about both our personal and professional lives – and then move on to formal models.

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Metacognition as a prerequisite for interdisciplinary integration

By Machiel Keestra

Machiel Keestra (biography)

What’s needed to enable the integration of concepts, theories, methods, and results across disciplines? Why is communication among experts important, but not sufficient? Interdisciplinary experts must also meta-cognize: both individually and as a team they must monitor, evaluate and regulate their cognitive processes and mental representations. Without this, expertise will function suboptimally both for individuals and teams. Metacognition is not an easy task, though, and deserves more attention in both training and collaboration processes than it usually gets. Why is metacognition so challenging and how can it be facilitated?

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