Social learning – Page 2 – Integration and Implementation Insights

Synthesis of knowledge about participatory modeling: How a group’s perceptions changed over time

September 11, 2024July 3, 2018

By Rebecca Jordan

How do a group’s perceptions change over time, when members across a range of institutions are brought together at regular intervals to synthesize ideas? Synthesis centers have been established to catalyze more effective cross-disciplinary research on complex problems, as described in the blog post ‘Synthesis centers as critical research infrastructure‘, by Andrew Campbell.

I co-led a group synthesizing ideas about participatory modeling as one of the activities at the National Socio-Environmental Synthesis Center (SESYNC). We met in Annapolis, Maryland, USA, four times over three years for 3-4 days per meeting. Our task was to synthesize what is known about participatory modeling tools, processes, and outcomes, especially in environmental and natural resources management contexts.

Three tasks for transdisciplinary bridge builders

September 29, 2021October 17, 2017

By Roderick J. Lawrence

roderick-lawrence — Roderick J. Lawrence (biography)

Human groups and societies have built many kinds of bridges for centuries. Since the 19^th century, engineers have designed complex physical structures that were intended to serve one or more purposes in precise situations. In essence, the construction of a bridge is meant to join two places together. What may appear as a mundane functional structure is built only after numerous decisions have been made about its appearance, cost, functions, location and structure. Will a bridge serve only as a link and passage, or will it serve other functions?

In discussing three things the transdisciplinary research community can do to build bridges, I use “building bridges” as a metaphor. I discuss a bridge as a human-made artefact that is attributed meaningful form. It is created intentionally for one or more purposes.

Impacts of social learning in transformative research

February 11, 2025May 16, 2017

By Flurina Schneider, Lara M. Lundsgaard-Hansen, Thoumthone Vongvisouk, and Julie G. Zähringer

authors_schneider_lundsgaard-hansen_vongvisouk_zahringer — 1. Flurina Schneider (biography)
2. Lara M. Lundsgaard-Hansen (biography)
3. Thoumthone Vongvisouk (biography)
4. Julie G. Zähringer (biography)

How can science truly support sustainability transformations?

In our research projects we often find that the very process of co-producing knowledge with stakeholders has transformative impacts. This requires careful design and implementation. Knowledge co-production in transdisciplinary and other research leads to social learning and can make a difference in the lives of those involved.

Knowledge co-production is, therefore, not only a cognitive endeavour that will result in new, action-oriented knowledge, but also a broad social learning process that includes relational, normative, and emotional dimensions.

The following three examples from recent research on sustainable land use and poverty alleviation in Laos and Myanmar illustrate how it can work.

Designing for impact in transdisciplinary research

February 18, 2025February 16, 2017

By Cynthia Mitchell, Dena Fam and Dana Cordell

authors_cynthia-mitchell_dena-fam_dana-cordell — 1. Cynthia Mitchell (biography)
2. Dena Fam (biography)
3. Dana Cordell (biography)

Starting with richly articulated pictures of where we would like to be at some defined point in the future has powerful consequences for any human endeavour. How can we use such “Outcome Spaces” to guide the conception, design, implementation, and evaluation of transdisciplinary research?

Our Outcome Spaces Framework (Mitchell et al., 2017) considers three essential impacts:

(1) improving the situation,
(2) generating relevant stocks and flows of knowledge, and
(3) mutual and transformational learning by the researcher/s and involved participants.

Learning through modeling

October 9, 2023November 17, 2016

By Kirsten Kainz

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.