Cutting Edge > Complex Systems > Coupled Systems Role-playing Exercise

A Role-Playing Approach to Coupled Complex Natural and Human Systems

This web page is based on a document produced by Jimm Myers and Greg Marfleet at the 2010 workshop on Developing Student Understanding on Complex Systems in the Geosciences. Jimm and Greg collaborated to produce this vision of how instructors might work together to incorporate an interdisciplinary approach to teaching complex systems, using a role-playing exercise in a pair of linked courses: a geoscience course and a political science or public policy course. In this example, the role-playing exercise focuses on how complex natural and human systems interact to define public policy governing environmental and resource issues.
Intersecting Complex Systems Diagram

Goals for this Exercise:

To demonstrate to students, through simulation, how complex natural and human systems interact to make policy. This overarching goal incorporates several other objectives, including illuminating how public policy is made, providing insights into how access to public policy making systems can be achieved, and preparing students with citizenship skills to tackle grand challenges.

Design:

We envision integrating two linked, dyad courses in a shared simulation experience lasting one or two weeks. One class would be a course in natural or earth science focused on complexity-based inquiry into natural processes (for example: Energy from a Scientific Perspective). The other would be a course in political science or public policy focused on exploring the tools of policy making (for example: Environmental Politics and Public Policy). The interaction between the students in these courses would serve to mirror the inherent problem of expertise in each domain. While the science students have extensive knowledge of natural systems and insights into complex causality, randomness, and uncertainty, they lack experience interacting with or manipulating policy making organizations. Policy students, while they have awareness of political and bureaucratic organizations and actors, lack specific scientific expertise.

Complex Multi-agent Network

Implementation:

Course 1: Science

The companion science course will focus on the natural system of interest, e.g. water, petroleum, etc. from an integrated science approach, i.e. biology, chemistry and Earth sciences. By exploring these systems as complex systems, the course will convey to the student that natural models of the real world are always characterized by uncertainty and complexity and that data collected to describe natural systems are always marked by randomness. As scientists they must convey this type of information to other stakeholders who are unlikely to be familiar with the complex nature of natural systems.

Course 2: Public Policy

In addition to its substantive content related to law, policy and institutions, the public policy course would include exploration of literature and/or models exploring the way multi-agent social network systems work. A key concept arising from this exploration would be that public policy making systems are complex and that policy may be understood as the emergent outcome of limited, constrained or myopic interacting agents each with a set of local connections.

The Simulation

Roughly two-thirds of the way through the semester, students from both courses would be presented with a significant public policy problem for which a government or IGO (intergovernmental organization) solution is required (ex. carbon tax, irrigation, invasive species). Students from the public policy class would be assigned to specific roles in the various relevant policy making organizations (bureaucratic agency staff, congressional liaisons, Executive offices staff, joint committee representatives, congressional staff positions, etc.) or to roles as stakeholders and policy advocates. Clear rules would govern the allowable communication and access between actors within this system. Most students in the science class could take on the role of 'scientific community' with expertise, while a few might also be assigned specific organizational positions (i.e President's science adviser, resident EPA scientist). In early stages of the simulation, high-level agents would consider the problem and direct lower-level members of the policy network to acquire and synthesize information through interviews with scientists and citizens/stakeholders. As the simulation progressed, higher-level members would amalgamate this collected information through interaction with subordinates and/or connected peers and begin to craft a policy response.

Assessment

Following the simulation, students would be asked to evaluate the public policy decision. Science students would consider the likely impact of the proposed human activity on the natural system, in light of their understanding, and would identify potential unexpected consequences. Public policy students, freed from their communications constraints, would investigate the information flows and lapses and evaluate the effectiveness of the policy making process. Both groups would be asked to explore how complexity impacted the way information was presented, shared or incorporated.

Independent evaluation of the use of complex systems concepts in these writings could be used to measure learning outcomes. Pre- and post-exercise surveys might also generate data on attitudes toward the intersection of natural and social environments.

Resources

Olivier Barreteau, Fran├žois Bousquet, and Jean-Marie Attonaty (2001). Role-playing games for opening the black box of multi-agent systems: method and lessons of its application to Senegal River Valley irrigated systems. Journal of Artificial Societies and Social Simulation, vol. 4, no. 2, available online at http://www.soc.surrey.ac.uk/JASSS/4/2/5.html.

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