Measuring and fostering interdisciplinarity: social GM vs. natural evolution

Recently, interdisciplinary research has received significant media attention. Governments and universities encourage interdisciplinary research, but various reports show that reality might be not so bright: research proposals that belong to several fields of research have lower funding success; governments are still figuring out how to access quality of interdisciplinary research outputs. What could help overcome these challenges? Our argument is simple: decisions about interdisciplinary research should be informed by a solid understanding of the (inter)disciplines and interdisciplinary work. What is “discipline” and what is “inter”? What does it mean to work in interdisciplinary boundaries? How do new disciplines and research fields emerge? To which extend methods from evolutionary biology could be applicable for “measuring” interdisciplinarity? Below is a copy our comment that we wrote in response to this paper published recently in Nature.

Video from the University of Sydney Charles Perkins Centre:

Understanding and stimulating interdisciplinary research can benefit from having reliable methods to measure its benefits and the challenges it faces. It is useful to be reminded that assessments of interdisciplinary research proposals often involve extra hurdles (Nature 534, 589–590; 2016) and to see how metrics from evolutionary biology can assist in detecting some anomalies (Nature 534, 684–687; 2016). However, the ‘species’ of research represented in schemes like The 2008 Australian and New Zealand Standard Research Classification do not evolve naturally. Indeed, such classification schemes are periodically modified to recognize and support new emerging (interdisciplinary) fields of R&D. For example, the 2008 ANZSRC recognizes a number of established and emerging interdisciplinary research fields, such as nanotechnology, interdisciplinary engineering, cognitive science and the learning sciences. Theoretical and methodological diversity and complexity within such interdisciplinary fields can be even higher than across other independently classified research fields. (Note, our examination of the raw data published in Nature (534, 684–687; 2016) shows that research proposal success rates in these four explicitly interdisciplinary fields are higher than in their ‘parent’ fields.) While the notion that disciplines are naturally evolving species can be useful in suggesting new ways of measuring interdisciplinarity, we must not forget that disciplines and classification systems are dynamic social constructs. One might say that research activity is open to ‘genetic modification’, taxonomies are renegotiated and – in subtle ways – taxonomies reshape the evolution of that which they classify. We are not arguing that current interdisciplinary research funding schemes do not need improvement, but if we are to be smart about assessing and fostering interdisciplinary, then we must pay close attention to the distinctly social nature of evolution in research.


Bromham, L., Dinnage, R., & Hua, X. (2016). Interdisciplinary research has consistently lower funding success. [Letter]. Nature, 534(7609), 684-687. doi: 10.1038/nature18315. Retrieved from

Some notes from the history of interdisciplinarity

Frank 1988 p 146

From Frank, 1988, p. 146

It is not difficult to notice that epistemic fluency has its roots in interdisciplinarity. But what are the roots of interdisciplinarity? Some historical writings trace the origins of interdisciplinarity back to the mid-1920s (Frank, 1988; Sills, 1986; Graff, 2015). These exquisitely written historical texts nicely show that interdisciplinarity has been one of most ambitious and challenging intellectual projects for more than nine decades. During this time, interdisciplinary has celebrated some great achievements, but equally often it has also struggled to fulfil its promises.

Yes, during last few years, interdisciplinarity (again) has become a hot topic and (again) made its way into research funding schemes and university’s curriculums. But let’s not forget that it has been trying to do so for 90 years. What astonishes is that we know so little about how people learn to do this complex work.

Below are some insights that worth knowing and/or not forgetting.

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Indexing Gratitude

I want to put on record my thanks to colleague and lead author Lina Markauskaite for her determination and skill in producing an exemplary index for the Epistemic Fluency book. A heroic undertaking, now completed. There may still be a few little odds and ends to sort out before the manuscript finally goes to print, but the index was the last big task.

Index snippet

Bridging professional learning, doing and innovation through making epistemic artefacts

We added to our slideware our presentation “Bridging professional learning, doing and innovation through making epistemic artefacts”, presented last week at the Practice-Based Education Summit “Bridging Practice Spaces” at Charles Sturt University. This presentation draws on the ideas from Chapter 8: Objects, things and artefacts in professional learning and doing of the book “Epistemic Fluency and Professional Learning“. It discusses how students’ work on making various artefacts for their assessments in courses that prepare them for professional practice bridges knowledge learnt in university setting with knowledge work in workplaces.

The gist of our argument can be summarised as follows:

  1. Professional expertise is inseparable from capacities to (co-)construct epistemic environments that enhance knowledgeable actions.
  2. Such expertise is grounded in embodied, situated professional knowledge work.
  3. Much of this work is done by (co-)creating epistemic artefacts that embody actionable knowledge.
  4. Productive epistemic artefacts connect the object (‘why’ of work) and the thing (‘what’ of work) through action (‘know how’) and ways of thinking that underpin situated professional innovation (ie. epistemic fluency)

In learning, much of the value of the epistemic artefacts comes from their dual and deeply entangled nature: they are simultaneously objective and grounded in situated experiences (aka. subjective). They embody actionable knowledge, and the activity through which they are constructed embodies knowledgeable action. They are reflective and projective.
Learning through making artefacts line

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Epistemic fluency perspectives in teaching and learning practice

How can epistemic fluency perspectives be enacted in daily learning and teaching work? This presentation overviews the design of a blended course Systems, Change and Learning that fundamentally builds on the ideas of epistemic fluency. The course draws together three modes of human inquiry: systems thinking, design practice and responsive action. Through reflective engagement with ideas from different disciplinary domains and teamwork on practical innovation challenges, students begin to appreciate the need to accommodate diverse perspectives and learn to combine diverse ways of knowing. This is not a “flagship” course – it never received any extra funding or other “external” support – but a course that emerged gradually through our daily work with students. By being “usual” and simultaneously “different” this course has celebrated students’ deep  engagement, collaboration and positive feedback. A brief description of our approach is in the presentation and this document. Below is a short summary.

three modes of inquiry

Summary: Learning to lead innovation and change

Capacities to drive collective learning,  jointly address complex practical challenges and create innovative solutions are seen as essential for future graduates. How can we prepare students to lead complex collaborative learning, change and innovation projects? How can we help them to develop the knowledge and skills needed for resourceful teamwork with other people who have different areas of expertise, experiences, and interests? Continue reading