Models as ‘interested amateurs’

By Pete Barbrook-Johnson

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Pete Barbrook-Johnson (biography)

How can we improve the often poor interaction and lack of genuine discussions between policy makers, experts, and those affected by policy?

As a social scientist who makes and uses models, an idea from Daniel Dennett’s (2013) book ‘Intuition Pumps and Other Tools for Thinking’ struck a chord with me. Dennett introduces the idea of using lay audiences to aid and improve understanding between experts. Dennett suggests that including lay audiences (which he calls ‘curious nonexperts’) in discussions can entice experts to err on the side of over-explaining their thoughts and positions. When experts are talking only to other experts, Dennett suggests they under-explain, not wanting to insult others or look stupid by going over basic assumptions. This means they can fail to identify areas of disagreement, or to reach consensus, understanding, or conclusions that may be constructive.

For Dennett, the ‘curious nonexperts’ are undergraduate philosophy students, to be included in debates between professors. For me, the book sparked the idea that models could be ‘curious nonexperts’ in policy debates and processes.

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Learning through modeling

By Kirsten Kainz

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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.

Consider the real-world case I was involved in of a meeting in a school district that intends to roll-out a new mathematics curriculum and support teachers’ use of the new curriculum through professional development. The district has made a large monetary investment in the curriculum and professional development both through the purchase of materials and the dedication of human resources to the effort.

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ICTAM: Bringing mental models to numerical models

By Sondoss Elsawah

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Sondoss Elsawah (biography)

How can we capture the highly qualitative, subjective and rich nature of people’s thinking – their mental models – and translate it into formal quantitative data to be used in numerical models?

This cannot be addressed by a single method or software tool. We need multi-method approaches that have the capacity to take us through the learning journey of eliciting and representing people’s mental models, analysing them, and generating algorithms that can be incorporated into numerical models.

More importantly, this methodology should allow us to see in a transparent way the progression on this learning journey.

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Can mapping mental models improve research implementation?

By Katrin Prager

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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.

Katie Moon and Vanessa Adams used a more elaborate approach to map natural resource managers’ mental models of invasive species management (2MB PDF available from linked page).

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