Addressing Complex Challenges of the World
In RC4, our students develop a sense of agency and a spirit of concern for the world. As caring and committed citizens, they employ systems thinking and interdisciplinary methods of inquiry to address complex challenges of our fast changing and highly interconnected world.
Systems Thinking
Systems thinking seeks solutions to challenging social, environmental, economic and public policy problem-areas facing humankind. Among problem-areas RC4 students may study are sustainable development, addiction, crime, economic cycles, conflict-development-linkages, cities growth and decline, spread of infections diseases, global development and many more. According to best-selling author, MIT Senior Fellow, Peter Senge, systems thinking offers theories and new vantage points that deepen our understanding of how such complex problems may be produced by interdependent phenomena that seem distant in time and space.
Mastery of systems thinking concepts represents an important, valuable first step on the path towards understanding the challenging problems humankind faces. However most leading scholar-practitioners in the field, especially including the creator of system dynamics modeling, MIT Professor Jay W. Forrester, believe it is only a first step.
Systems Dynamics Modelling
Gaining some mastery of system dynamics modeling is a vitally important second step. John Sterman, who holds the J.W. Forrester Chair at MIT's Sloan School of Management, explains why. In his foundational text, Business Dynamics: Systems Thinking and Modeling for a Complex World, Sterman writes: "The challenge facing us all is how to move from generalizing about accelerating learning and systems thinking to tools and processes that help us to understand complexity, design better operating policies and guide change in systems from the smallest business to the planet as a whole. We are all passengers on an aircraft we must not only fly but redesign in flight. Just as an airline uses flight simulators to help pilots learn."
Sterman concludes: "Successful approaches to learning about complex dynamic systems require:
- Tools to elicit and represent the mental models we hold about the nature of difficult problems
- Formal models and simulation methods to test and improve our mental models
- Methods to sharpen scientific reasoning skills, improve group processes and overcome defensive routines for individuals and teams."
