By Emma Ligtermoet, Claudia Munera-Roldan, Cathy Robinson, Zaynel Sushil and Peat Leith.
What forms of learning can support interdisciplinary teams to rapidly build reflexivity capabilities, especially in preparation for doing transdisciplinary (engaged) science with non-researcher societal actors?
Transdisciplinary co-production requires deep and reflexive learning. Reflexivity is a key capability for researchers doing inter- and transdisciplinary science, involving the critical enquiry of existing assumptions, values and norms underlying our decisions and actions, with the aim to adapt or change current practices or discourses.
Such learning is foundational for understanding and proactively engaging with knowledge-power dynamics, including potentially catalysing shifts in incumbent dynamics when preparing to engage with non-societal actors. This is particularly critical in sustainability science and other areas where the focus is to drive transformative societal change. It requires a depth of understanding of the context and positioning of the research, through working with those who have a stake in the particular transformative societal change.
We built a framework comprising four learning domains: cognitive, epistemic, normative and relational. To do this we synthesised learning theory from social learning and transdisciplinary science.
In the figure below, we also show how the four learning domains align conceptually with the principles of co-production; in particular knowledge co-production requires:
- learning new things (cognitive learning),
- at the same time as working together with partners and learning from each other (relational learning),
- often across diverse knowledge systems (requiring epistemic learning),
- and a critical understanding of the values and assumptions that the work rests upon or seeks to change (normative learning).
The last three learning domains are particularly important in research that seeks to drive transformative societal change in sustainability and other areas (the target in the middle of the figure).
We also related the four learning domains to a framework described in our i2Inisghts contribution “Preparing interdisciplinary research teams for transdisciplinary co-production: a framework and diagnostic questions”. In this framework, context is used to centre exploration of interconnected elements of positionality, purpose, power and process (4Ps).
To reiterate briefly:
- Context characterises the scope, operating space, intervention or research setting of the project.
- Positionality provides understanding of the multi-layered characteristics that make up individuals and the team.
- Purpose is about arriving at a shared understanding among the team of both the research purpose and the purposes for engaging in co-production with societal actors.
- Power requires making visible and transparent the variety of power differences that exist within research collaborations and among broader societal actors.
- Process establishes the operating conditions and builds the collective learning environment.
We related the four learning domains to the context-centred 4Ps knowledge co-production framework by working with interdisciplinary research teams that were at early stages of sustainability science projects at Australia’s national science agency, CSIRO, by road testing methods for enabling critical co-production capabilities. We found that:
- Epistemic and relational learning are necessary at the intersection of positionality and purpose in order to embrace pluralism. Where researchers came to understand epistemic diversity within their team they often did this most effectively through activities that enabled team reflection on positionality and purpose for co-producing, followed by consideration of which stakeholders should be engaged, and why.
- Cognitive learning appeared necessary to understand contextual characteristics and methodologies required to generate new knowledge, particularly as teams grappled with new contexts, as well as co-production concepts.
- Relational learning supported interactive enquiry within diverse teams, and while discussions generated by all four Ps provided relational learning opportunities, they often arose during process-focused discussions.
- Normative learning highlighted values attached to particular methods, roles or processes and can drive innovative sustainability outcomes through consolidation in building shared goals, values and directions or options for activity.
The interactivity between modes of learning and the context-centred 4Ps knowledge co-production framework points to numerous ways that cognitive, relational, epistemic and normative learning can layer, buttress and support each other, applying critical co-production thinking to develop readiness for co-production.
We concluded that reflexive learning is an early indicator of the success of embedding critical co-production capabilities within a research team or project. This is, in part at least, because members of interdisciplinary teams will have different perspectives, capabilities, philosophies and methodologies that they bring to the research.
How do you create learning opportunities in your teams as they tackle co-production with societal actors? Do you use similar learning domains or others? Does our experience with the particular value of these learning domains resonate with your experience?
Use of Generative Artificial Intelligence (AI) Statement: Generative artificial intelligence was not used in the development of this i2Insights contribution. (For i2Insights policy on generative artificial intelligence please see https://i2insights.org/contributing-to-i2insights/guidelines-for-authors/#artificial-intelligence.)
Emma Ligtermoet PhD is a human-environment geographer and postdoctoral research fellow at CSIRO’s Valuing Sustainability Future Science Platform. She is based in Perth, Australia. Her research applies knowledge co-production theory and practice to understand socio-ecological change and just governance in navigating transitions and adaptation.
Claudia Munera-Roldan PhD is an interdisciplinary postdoctoral research fellow at CSIRO’s Valuing Sustainability Future Science Platform, based in Canberra, Australia. Claudia works at the interface of science-policy-practice in environmental governance arrangements, co-production, and futures. She applies future-oriented approaches, exploring options towards strategic thinking and collective learning to navigate global changes, considering the linkages between local communities and private and public sector initiatives to find options towards sustainable futures.
Cathy Robinson PhD is the project lead at CSIRO for Valuing Local Provenance which focuses on how to support locally defined co-benefits into emerging sustainability markets. Based in Brisbane, Australia, her research as a social and sustainability scientist has been applied through a range of Indigenous-led initiatives that show how to accelerate innovation with ideas that empower Indigenous knowledge, on-country enterprises and communities.
Zaynel Sushil MSc is an impact entrepreneur and strategist at CSIRO, based in Brisbane, Australia. He has a track record of launching and scaling social enterprises and is currently working on CSIRO initiatives including the Ag2050 Caring for Country and the Agricultural Productions Systems Simulator.
Peat Leith PhD leads CSIRO’s Valuing Sustainability Future Science Platform and is project lead for the Sustainability Science Scaffolding Project. He is based in Canberra, Australia. His research background as a social scientist in natural resource management across marine and coastal zone management, and agriculture, has focussed on how science can effectively underpin sustainability outcomes.
I love this, it is super helpful and encompasses a lot of experience in co-production in many domains. One additional challenge – where does the “conversation” with the biosphere/Country come into this? An aspect of the relational domain?
Thanks Ro! What an excellent exploratory question for interdisciplinary teams! Yes, I would also see it largely within relational learning domain, perhaps flowing on from the sharing of researcher standpoints made visible through the positionality work (of the 4 P’s preparing for co-production)? The researcher positionalities within the team would shape the degree of normative and epistemic learning involved also, in getting heads around potential researcher roles in facilitating or shaping that ‘conversation’ with biosphere/Country. The layering of learning domains effect? And this conservation with biosphere/Country is clearly context-sensitive, so it could emerge from understanding the context framing too.
Thank you for your posts. Both parts 1 and 2 read together are illuminating. They certainly resonated with my experience as a researcher in social-ecological systems, where I see the value of placing more focus than there currently is on the social and reflexive learning aspects, and how diverse forms of knowledge and information that underpins learning flows within transdisciplinary teams or networks.
I also think that the creation of more ‘safe spaces’, particularly at the beginning of td projects, in the form of regular informal meet-ups helps build the strong relational learning aspects i.e. trust, openness, empathy required for deep learning experiences across diversity and complexity. This goes a long way towards nurturing all types of learning and reflexivity.
Hi Faye, Great to hear the posts resonated with you! I totally agree- this exploratory work and working in inter and trans-disciplinary research can be uncomfortable or even deeply unsettling for the ways we understand the world and our research approaches. It does need care and the building of trust, as well as researcher willingness to be open to potential unsettling. Regular informal meetups would be wonderful- face to face always preferable, though in this work it had to be via online means, as our teams were dispersed across the country. Online can certainly be harder for building those trusting spaces. I also wondered if ‘care’ could have also been an additional pillar supporting the collective learning environment, though saw it as related to trust- possibly both a precursor for and outcome of trust? Thanks for your interest. 🙂