Learning through modeling

By Kirsten Kainz

kirsten-kainz
Kirsten Kainz (biography)

How can co-creation communities use models – simple visual representations and/or sophisticated computer simulations – in ways that promote learning and improvement? Modeling techniques can serve to generate insights and correct misunderstandings. Are they equally as useful for fostering new learning and adaptation? Sterman (2006) argues that if new learning is to occur in complex systems then models must be subjected to testing. Model testing must, in turn, yield evidence that not only guides decision-making within the current model, but also feeds back evidence to improve existing models so that subsequent decisions can be based on new learning.

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Collaboration, difference and busyness

By Gabriele Bammer

gabriele-bammer
Gabriele Bammer (biography)

What are the ingredients of successful research collaboration? How can we make collaboration work when we are all getting busier?

One of the best guides to success in collaborative team work was produced by Michelle Bennett, Howard Gadlin and Samantha Levine-Findlay in 2010. Built on the experience of researchers at the US National Institutes of Health, they explored: preparing for collaboration, selecting team members, fostering trust, sharing credit, handling conflict and more.

An additional way of thinking about collaboration that I have found useful (Bammer 2008) is to consider it as a process of harnessing and managing differences.

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From integration to interaction: A knowledge ecology framework

By Zoë Sofoulis

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Zoë Sofoulis (biography)

Would a focus on ‘knowledge ecology’ provide a useful alternative to ‘knowledge integration’ in inter- and trans-disciplinary research?

My experience in bringing perspectives from the humanities, arts and social sciences (HASS) to projects led by researchers from science, technology, engineering and mathematics (STEM) has led me to agree with Sharp and colleagues (2011) that ‘knowledge integration’ is essentially a positivist concept, dependent on the idealist model of a unified field of scientific knowledge to which every bit of science contributed.

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Social science identities in interdisciplinary research and education

By Eric Toman

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Eric Toman (biography)

What does it mean to include ‘a social scientist’ in a team tackling complex problems? Here I focus on complex environmental problems and how biophysical and social scientists work together. I’m curious if social scientists face the same issues in other problem areas, such as health.

Things have improved since my early academic career, when I was often asked to justify why a social scientist deserved a seat at the table when discussing environmental questions. It seemed that even supportive natural scientists were motivated to engage their social science colleagues only to ‘fix’ some type of problem caused by people (e.g., politicians, decision-makers, managers, the “general public”).

While it’s now normal for social scientists to be included, they tend to be lumped together, unlike the biophysical scientists who are differentiated into a range of disciplines with relevant specialization areas.

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In praise of multidisciplinarity

By Gabriele Bammer

gabriele-bammer
Gabriele Bammer (biography)

What characterizes multidisciplinary research? When is it most appropriate? What does it take to do it well? Multidisciplinarity often gets a bad rap, being seen as less sophisticated than interdisciplinarity and transdisciplinarity. But does it have its own important role in dealing with complex social and environmental problems?

Multidisciplinary research has two primary characteristics:

  1. different disciplines independently shine their light on a particular problem, and
  2. synthesis happens at the end and can be undertaken by anyone.

Unlike interdisciplinary and transdisciplinary research, there is no attempt to agree upfront on either a problem definition or on how the different perspectives will be brought together.

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Integrating disciplines / Integrando disciplinas

By Marcel Bursztyn, Gabriela Litre and Stéphanie Nasuti

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Marcel Bursztyn (biography)

An English version of this post is available

Como conseguir que um grupo multidisciplinar integrado por economistas, climatologistas, geógrafos, antropólogos, biólogos, sociólogos, jornalistas, engenheiros químicos, engenheiros ambientais e advogados trabalhe de maneira mais interdisciplinar?

gabriela-litre
Gabriela Litre (biography)

Esse foi o desafio encarado por um projeto de pesquisa sobre as percepções de agricultores familiares de quatro biomas brasileiros (a Amazônia, o Cerrado, o Pantanal e o Semiárido) sobre os impactos que as mudanças climáticas estão tendo nos seus modos de vida. Esse pequenos produtores, com baixa disponibilidade de capital, estão expostos a riscos naturais e socioeconômicos, e são extremadamente vulneráveis aos eventos climáticos extremos.

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Stéphanie Nasuti (biography)

Um fator chave foi a demarcação do marco teórico do projeto, que incluiu a hipótese de que o sucesso das politicas de adaptação aumenta consideravelmente quando essas políticas se baseiam em um conhecimento de primeira mão das realidades cotidianas e das percepções das populações envolvidas.

O desenho da pesquisa foi guiado por três elementos básicos:

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Five steps for managing diversity to create synergy

By Doug Easterling

doug-easterling
Doug Easterling (biography)

How can we address social, environmental, political and health problems that are too big and too complex for any single person, organization or institution to solve, or even to budge? How can we pool our wisdom and work collaboratively toward purposes that are larger than ourselves?

In theory at least, co-creation generates innovative solutions that transcend what would otherwise be produced by the participants acting on their own. In other words, co-creation can foster synergy.

To maximize synergy, a co-creative group should include participants who understand the problem from all the relevant perspectives. The more complex the problem, the greater the number and diversity of stakeholders who should be included in the process. A broader range of perspectives and ways of thinking allows for a richer and more comprehensive analysis of the problem, as well as more innovative solutions that address more of the underlying factors.

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Why participatory models need to include cultural models

By Michael Paolisso

michael-paolisso
Michael Paolisso (biography)

Participatory modeling has at its heart the goal of engaging and involving community stakeholders. It aims to connect academic environments and the communities we want to understand and/or help. Participatory modelling approaches include: use facilitators, provide hands-on experiences, allow open conversation, open up the modeling “black box,” look for areas of consensus, and “engage stakeholders” for their input.

One approach that has not been used to help translate and disseminate participatory models to non-modelers and non-scientists is something psychologists and anthropologists call “cultural models.” Cultural models are presupposed, taken-for-granted understandings of the world that are shared by a group of people.

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Can mapping mental models improve research implementation?

By Katrin Prager

katrin-prager
Katrin Prager (biography)

We all have different mental models of the environment and the people around us. They help us make sense of what we experience. In a recent project exploring how to improve soil management (PDF 250KB), Michiel Curfs and I used data collected from Spanish farmers and our own experience to develop and compare the mental model of a typical Spanish farmer growing olives with that of a hypothetical scientist. How did their mental models of soil degradation differ? Mainly in terms of understanding the role of ploughing, and the importance of drivers for certain soil management activities. There were only a few areas of overlap: both scientist and farmer were concerned about fire risk and acknowledged weeds. We emphasise the importance of two-way communication, and recommend starting by focusing on areas of overlap and then moving to areas that are different. Without integrating understandings from both mental models, the scientist will carry on making recommendations for reducing soil degradation that the farmer cannot implement or does not find relevant.

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