Metacognition as a prerequisite for interdisciplinary integration

Community member post by Machiel Keestra

Machiel Keestra (biography)

What’s needed to enable the integration of concepts, theories, methods, and results across disciplines? Why is communication among experts important, but not sufficient? Interdisciplinary experts must also meta-cognize: both individually and as a team they must monitor, evaluate and regulate their cognitive processes and mental representations. Without this, expertise will function suboptimally both for individuals and teams. Metacognition is not an easy task, though, and deserves more attention in both training and collaboration processes than it usually gets. Why is metacognition so challenging and how can it be facilitated?

Understanding cognitive processes and representations

Whenever we engage with any cognitive or behavioral tasks, our brain employs a mental representation or knowledge structure that corresponds to a word, image, or other information pertaining to that task. Experience contributes to further enrichment and structuring of that representation. A beginner’s mental representation of a new word (‘space shuttle’, eg.) may thus contain just its letters and an image of the object, yet additional experience and information is automatically cognitively integrated with that representation, providing associations with mental representations of shuttle parts, of launching and landing actions, images and so on.

The superior performance of experts relies upon their having assembled many more, and more complex, mental representations pertaining to their field of expertise. Examples range from accurate and fast recognition, recall and processing by chess masters of a large number of complex chess positions, the complex sequences of movements of musicians playing by sight, fast strategic decisions by sport champions, and immediate detection of a mistake in a function by mathematicians.

Importantly, we do not need to learn those mental representations explicitly, nor are we often able to make them explicit once we have learned them. Indeed, we usually acquire and employ them automatically and implicitly in our cognition and behavior: for example, young children don’t explicitly learn grammatical rules yet can use them well.

Problems with expertise

Handy as such automatic and implicit handling may be, it also contributes to ‘brittleness’ and other flaws of individual expertise. In particular, experts:

  • are overconfident in exceptional situations
  • often demonstrate a bias or fixedness towards habitual responses
  • tend to rely upon their expertise in neighbouring yet different domains
  • often display a lack of creativity compared to beginners.

These are direct consequences of the cognitive processes upon which expertise rests and the knowledge structures or mental representations that are involved in those processes.

Particularly relevant for interdisciplinarity is the disappointing fact that expertise can make it more difficult for us to recognize how the insights from an expert in another domain can be added to our knowledge or performance. Making our cognitive processes and representations explicit by metacognizing is a requisite for recognizing implicit assumptions and for acknowledging gaps in knowledge and methods that another expert might help to fill, as shown in the first figure below.

An expert engages in meta-cognition about their thinking and knowing. Here, the expert reflects specifically about their learning process (in the cloud) and the set of representations it has yielded. Such reflections also prepare them for the integration of an additional insight from another expert, such as the green square added here (from Keestra 2017: 142).

Team collaboration and metacognition

Adding another level of complexity to this situation in the case of team work is the fact that experts automatically develop mental representations related to their team work, in addition and connected to those pertaining to their individual expertise. These representations concern the ‘who, what, why, when, and how’ of the team, containing information about the team itself, its task, process-related information and representation of its overarching goal.

Team mental representations bring along similar risks to those mentioned above. For example, overlapping representational contents that are shared by all team members are quickly recognized and tend to dominate joint cognition and actions. Analogous to an individual expert’s bias, a team risks slipping into groupthink when it does not engage in team metacognition.

For team members to recognize and make effective use of each other’s non-overlapping representations and skills, in contrast, requires extra time and effort devoted to team metacognition in addition to individual metacognition, as represented in the figure below.

An interdisciplinary team of experts together develops a more comprehensive understanding of a phenomenon – represented by the three-dimensional cube composed of different elements each of them contributes. Their joint or team meta-cognition upon their interdisciplinary collaboration facilitates the process of their development of an interdisciplinary integration of their distinct mental representations of the phenomenon (from Keestra 2017: 156).

Working in a team also has metacognitive benefits. Being confronted with the metacognitive self-reflections and the self-regulatory strategies of others and receiving feedback from them can help in recognizing and articulating individual metacognition. In addition, individuals can feel more motivated to metacognize when functioning in teams.

However, to have such results team metacognition must be adequately guided in order to avoid unnecessary confusion, which can be exacerbated when status and cultural differences are insufficiently addressed. Adequately planning research phase-specific rounds of metacognition is important. Team leaders should formulate relevant prompts or questions to elicit the required individual and team metacognitive reflections and discussions.

Useful prompts

A few prompts are listed here; more can be found in an appendix to Keestra (2017):

  • What added value could research from the humanities/social sciences/sciences have for your research?
  • Why do you think that the task you propose to perform is optimal for solving the problem at stake? Would an alternative route be possible? Do you have doubts about the routes proposed by others?
  • Of all the features of the problem under scrutiny (as perhaps represented in a figure), what does and what does not make sense from your disciplinary perspective? Or what is especially difficult to understand? What would you like to know more about?
  • What goals have you as a team determined and what is the plan for reaching those goals? What are the issues that might arise with the current plan? Do your answers to these questions vary among individual team members?
  • Did new insights emerge or a new situation present itself to the team, that makes you feel you should revisit some of your previous personal contributions to the team work?

Conclusion

What has your experience been with metacognition challenges in interdisciplinary work? Have you ever seen or experienced groupthink? Are there other prompts that you have found useful? How have you incorporated metacognition in an interdisciplinary team project?

To find out more:
Keestra, M. (2017). Meta-cognition and reflection by interdisciplinary experts: Insights from cognitive science and philosophy. (With an appendix of prompts or questions for metacognition). Issues in Interdisciplinary Studies, 35, 121-169. Online (abstract): https://eric.ed.gov/?q=keestra&id=EJ1193675

Further reading:
Wiltshire, T. J., Rosch, K., Fiorella, L. and Fiore, S. M. (2014). Training for collaborative problem solving: Improving team process and performance through metacognitive prompting. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 58, 1: 1154-1158. Online (DOI): https://doi.org/10.1177/1541931214581241

Biography: Machiel Keestra PhD is a tenured assistant professor of philosophy at the Institute for Interdisciplinary Studies at the University of Amsterdam, the Netherlands. He teaches philosophy of science and interdisciplinary research in the Natural and Social Sciences bachelor and in the Brain and Cognitive Science master programs. He is a researcher at the Institute for Logic, Language and Computation, focusing on the philosophy of cognitive neuroscience. He is past-president of the international Association for Interdisciplinary Studies (AIS) and co-chairs the upcoming AIS conference on ‘Interdisciplinarity in Global Contexts’, October 24-26, 2019, in Amsterdam.

Embracing tension for energy and creativity in interdisciplinary research

Community member post by Liz Clarke and Rebecca Freeth

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Liz Clarke (biography)

Tensions inevitably arise in inter- and transdisciplinary research. Dealing with these tensions and resulting conflicts is one of the hardest things to do. We are meant to avoid or get rid of conflict and tension, right? Wrong!

Tension and conflict are not only inevitable; they can be a source of positivity, emergence, creativity and deep learning. By tension we mean the pull between the seemingly contradictory parts of a paradox, such as parts and wholes, stability and chaos, and rationality and creativity. These tensions can foster interpersonal conflict, particularly when team members treat the apparent contradictions as if only one was ‘right’. Continue reading

Skilful conversations for integration

Community member post by Rebecca Freeth and Liz Clarke

Rebecca Freeth (biography)

Interdisciplinary collaboration to tackle complex problems is challenging! In particular, interdisciplinary communication can be very difficult – how do we bridge the gulf of mutual incomprehension when we are working with people who think and talk so very differently from us? What skills are required when mutual incomprehension escalates into conflict, or thwarts decision making on important issues?

It is often at this point that collaborations lose momentum. In the absence of constructive or productive exchange, working relationships stagnate and people retreat to the places where they feel safest: Continue reading

Collaboration and team science: Top ten take aways

Community member post by L. Michelle Bennett and Christophe Marchand

l-michelle-bennett
L. Michelle Bennett (biography)

What are the key lessons for building a successful collaborative team? A new version of the Collaboration and Team Science Field Guide (Bennett et al., 2018) provides ten top take aways:

1. TRUST
It is almost impossible to imagine a successful collaboration without trust. Trust provides the foundation for a team. Trust is necessary for establishing other aspects of a successful collaboration such as psychological safety, candid conversation, a positive team dynamic, and successful conflict management. Continue reading

What can interdisciplinary collaborations learn from the science of team science?

suzi-spitzer
Suzi Spitzer (biography)

Community member post by Suzi Spitzer

How can we improve interdisciplinary collaborations? There are many lessons to be learned from the Science of Team Science. The following ten lessons summarize many of the ideas that were shared at the International Science of Team Science Conference in Galveston, Texas, in May 2018.

1. Team up with the right people
On the most basic level, scientists working on teams should be willing to integrate their thoughts with their teammates’ ideas. Participants should also possess a variety of social skills, such as negotiation and social perceptiveness. The most successful teams also encompass a moderate degree of deep-level diversity (values, perspectives, cognitive styles) and include women in leadership roles. Continue reading

Interdisciplinarity and evil – Understanding incommensurability

Community member post by J. Britt Holbrook

J. Britt Holbrook (biography)

Incommensurability is a recognized problem in interdisciplinary research. What is it? How can we understand it? And what can we do about it?

What is it?

Incommensurability is best illustrated by a real example. I once co-taught a class with a colleague from another discipline. Her discipline depends on empirical analysis of data sets, literally on counting things. I, on the other hand, am a philosopher. We don’t count. One day she said to our students, “If you don’t have an empirical element in what you’re doing, it’s not research.” I watched the students start nodding, paused for half a beat, and volunteered, “So, I’ve never done any research in my entire career.” “That’s right!” she replied, immediately, yet hesitating somewhere between a discovery and a joke. Continue reading