Learning across disciplines in socio-environmental problem framing

Abstract

Modelling complex socio-environmental problems requires integration of knowledge across disparate fields of expertise. A key challenge is understanding how social learning across disciplines occurs in scientific research teams, in order that integrated knowledge is co-created. This article introduces a new framework for training researchers to integrate their knowledge across disciplines, based on current understanding of how inter- and transdisciplinary learning in research teams occurs. The framework was generated from a synthesis of learning, cognitive, and social science theories, and combines facilitated, structured negotiation processes with co-creation of boundary objects. It was used in two, 9 to 10-day intensive training workshops for doctoral students. This article describes the framework, workshop design, analysis of data collected during the workshops related to knowledge integration processes, what has been learned from the results, and the impact on participants. All participants indicated the experience was transformative, provided knowledge and skills unavailable elsewhere, filled gaps in their graduate education programs, and improving confidence in their capacity for inter- and transdisciplinary research. Pre- and post-workshop surveys confirm that the framework changed participants’ knowledge, behaviors, and competencies for engaging across disciplines. Many students have reported they have used the framework in a variety of other research and education settings, indicating they are able to transfer their new competencies to other contexts. Findings contribute to understanding of how to more effectively train researchers to integrate knowledge across disciplines for complex societal problem solving.

Epistemic stability and epistemic adaptability: interdisciplinary knowledge integration competencies for complex sustainability issues

“…They describe an interdisciplinary program for PhD students who conduct individual PhD research in a specialized field while working in parallel in a cross-disciplinary team. Moreover, our findings stress the need to explicitly train students in competencies for interdisciplinarity, which requires not only acquiring knowledge about interdisciplinarity, but also gaining experience in interdisciplinarity to acquire skills (Bridle et al 2013;Pennington et al 2021), and reflection to develop an attitude that supports interdisciplinary teamwork (Parker 2010). To raise awareness of disciplinary differences that was quite commonly lacking in our cohort, as became clear from the students with naïve behaviour, one could use approaches such as the Toolbox dialogue method (Hubbs et al 2020), as applied by Kjellberg et al (2018) to support the development of interdisciplinary consciousness and by Pennington et al (2021) to expose differences in epistemological assumptions to aid interdisciplinary teamwork.…”

Navigating Difference in Inter- & Transdisciplinary Learning

“…These fi ndings are in line with earlier fi ndings that emphasise the importance of learning inter-and transdisciplinarity through practice (e.g. Pennington et al, 2021). The involvement of teaching staff from a department specialised in inter-and transdisciplinary research and education enabled us to implement these strategies, echoing previous reports about the importance of teachers' abilities (Acevedo-Osorio et al, 2020;.…”

“…It has been shown that learning to engage in inter-and transdisciplinarity can be achieved through doing and experiencing inter-and transdisciplinary collaboration in practice (e.g. Freeth & Caniglia, 2020;Pennington et al, 2021). Moreover, learning about inter-and transdisciplinarity from theory has also been reported to contribute to learning to engage in inter-and transdisciplinary learning (e.g.…”

“…Moreover, learning about inter-and transdisciplinarity from theory has also been reported to contribute to learning to engage in inter-and transdisciplinary learning (e.g. Pennington et al, 2021).…”

Interdisciplinary Inquiry and Spatial Green Stormwater Infrastructure Research

“…This makes participatory modeling particularly flexible for bridging cross-disciplinary knowledge, ranging from problem conceptualization, assumed system components, and methodological approaches, the three categories of epistemological approach addressed in this paper. There are many examples of the process of co-creating model representations of socio-ecological systems [91]. These examples illustrate how both conceptual and computational models can be used to facilitate in-depth transdisciplinary discussions about appropriate resolutions, processes/dynamics that need to be represented, important system outputs, and system components [94,95].…”