Methods of transdisciplinary research

Project leader Prof. Dr. Ulli Vilsmaier

Transdisciplinary research has emerged as a research practice in a variety of knowledge fields (e.g. environmental science, development studies, education) since the 1990s. In 1994, Gibbons et al. (1994) introduced their concept of Mode 2 research as a strongly contextualized research practice in a particular field of application, characterized by heterogeneity, social accountability, reflexivity and transdisciplinarity (1994). Framed as a “new production of knowledge” and set apart from standard research practices (which the authors refer to as Mode 1), this kind of knowledge production was soon labeled “transdisciplinary.” In the context of sustainability science, transdisciplinary research aims to create stronger links between knowledge production and societal transformation (Lang et al. 2012; Vilsmaier & Lang 2014). It is assumed that contextualized research (i.e. research with strong links to societal spheres/actors) allow for a better understanding of complex problems as it takes a plurality of perspectives into account and links abstract and case-specific knowledge in order to develop knowledge and practices that serve sustainable development through learning and negotiation (Pohl & Hirsch Hadorn 2007; Krohn 2010; Jahn et al. 2012). Transdisciplinary research is also regarded as a promising strategy to overcome contractions caused by disciplinary boundaries (Mittelstraß 2003), and to overcome the outdated myth that science is an isolated, objective knowledge system (Nowotny 1999) at the core of society. These heterarchical research practices (Gibbons et al. 1994) aim to integrate diverse qualities of knowledge, gained through qualitative or quantitative research or every day practices, experiences or intuitions (Scholz & Tietje 2002; Pohl et al. 2008; Scholz 2011).

They also aim to overcome the division of societal domains at times when pressing societal sustainability problems call for cooperation. A science for society should transform towards a science with society (Scholz 2011) by creating spaces for joint knowledge production and societal transformation. In current transdisciplinary research approaches, a range of participation and assessment methods are applied and combined with established methods of empirical data collection, interpretation or modeling (examples see: Bergmann et al 2012; Hirsch Hadorn et al. 2008; Jahn 2008; Stauffacher et al. 2008; Scholz & Tietje 2002). However, there are critical epistemological and methodological concerns regarding both the Mode 2 discussion and the diverse set of transdisciplinary research practices. Zierhofer and Burger (2007) have studied a series of transdisciplinary research projects, concluding that, from an epistemological point of view, transdisciplinary research cannot be regarded as a specific mode of knowledge production, but a heterogeneous conglomeration of different research activities. Weingart (2005) discusses the Mode 2 debate against the background of the tension between the search for knowledge and useful application as a traditional dynamic of modern science since Bacon. Accordingly, the novelty of Mode 2 practices is historically invalid but indicates simply an adjustment of priorities. The crucial point of usability is its interrelatedness with interests and values. Currently, forms of transdisciplinary research aim to link scientific knowledge production not only with other qualities/forms of knowledge, but explicitly with interests and norms in order to provide solutions that are applicable to the goal of moving towards more sustainable forms of development.

There are many open questions in the context of transdisciplinary research practices and their role in establishing sustainability science as a guide to sustainable development that we will explore as part of this project. These include the exact nature of the integration of societal goals and values into the fabric of established scientific methods, determining the areas for which such a practice is indeed adequate, establishing methodological criteria for evaluating and integrating different types of input—not just data, but also values, norms and believes, assessing the epistemological status of the kind of knowledge generated by these practices, or the practical challenge connected to organizing such extended networks of knowledge production.