How to Teach Using Simulations & Systems
Serious games provide a new way to learn about complex systems. MIT's David Keith describes how instructors can "drive the future."
Most business schools teach an “open-loop” planning model, in which problem-solving moves through linear stages. MIT Sloan’s LearningEdge
initiative takes a different approach.
Open-loop thinking argues that problem solving moves through stages of identifying goals, gathering data, evaluating alternatives, and implementing solutions.
But the real world is complex and uncertain. Often managers lack full information and conditions change quickly. Actions lead to unpredictable reactions. “We make decisions, they have consequences, they change the state of the world, and they influence our decisions subsequently,” Keith explained. “This is continuous, emergent, potentially nonlinear behavior.”
As a result, decision-makers must understand the broader system
, not just a few isolated elements. And, they need to be prepared to act dynamically. For example, a person driving a car can map the direction to a restaurant, but must be able to adapt in real time to road closure or a traffic jam.
LearningEdge develops “management flight simulators
,” similar to aircraft flight simulators, as a way of communicating real-world complexity. Simulators try to put students “in a situation where they are facing the same challenges as the real decision-makers,” said Keith. The goal: help them build understanding of systems challenges that they will apply once in the workforce.
The instructor becomes a “guide on the side” rather than the traditional “sage on the stage.” Management simulators encourage rapid experimentation. Students direct their own learning, owning the outcomes. Simulations are not toys, Keith said. “These are the best empirically grounded models that we can develop.”
- Driving the Future: A Simulator of the US Automobile Fleet
- CleanStart: Simulating a Clean Energy Startup
- Eclipsing the Competition: The Solar PV Industry Simulation
- Fishbanks: A Renewable Resource Management Simulation
- World Climate: Negotiating a Global Climate Change Agreement
- World Energy: A Climate and Energy Policy Negotiation Game
Each comes with materials for instructors, including video teaching notes and slides. Simulations can be scheduled for 60-120 minutes, and involve 4-100 participants.
Do simulations lead to better learning outcomes than traditional educational approaches? “Participants say they are just more interesting, more engaging,” said Keith. His research
shows that short-term learning outcomes are greater than in more passive forms of education (e.g., reading a report about the simulation results). However, he doesn’t yet know if the knowledge acquired via a simulation persists, or if this knowledge helps participants make better decisions outside the classroom. Anecdotally, Keith believes that the simulators develop problem-solving skills, and highlight the challenge of changing complex and slow-moving systems.
Keith showed workshop participants how an instructor might use a simulation in the classroom. The Driving the Future
simulation draws on Keith’s extensive research in the auto industry. Users explore the strategy and policy levers that influence the diffusion of Alternative Fuel Vehicles (AFV) in the United States through 2050. The player is the U.S. “car czar,” with the job of managing the fleet.
Instructors begin by framing the problem. They can use a few slides, with videos and readings for additional background. For Driving the Future, the background framing is that AFV adoption (currently one per cent of US auto sales) is too low to meet energy and environmental goals.
Instructors can involve students by either:
- Having each student work through a pre-defined set of scenarios
- Dividing the class into groups representing different industry stakeholders (NGOs, car industry, government, fuel industry), and asking each to find the mix of policies and strategies they think best serves their stakeholder’s interests
In Driving the Future, students can change incentives, ads, taxes, and fuel pricing. Their actions lead to shifts in various metrics representing the “state of the world.”
In a 90-minute class, Keith generally saves 30 minutes for intro and debrief.
Here’s what Keith hears from students after they participate in the simulation:
- It’s much harder to effect change than they thought. Systems move slowly. Even with huge flows of money (e.g. incentives and taxes), the large stock of existing vehicles won’t turn over quickly. An average U.S. vehicle lasts for 16 years; shifting all cars to electric would take more than 20 years even if 100% of new vehicles sold were electric starting today.
- Many interacting factors determine change. For AFV adoption, these factors include consumer education, recharging infrastructure, available vehicles, and supportive policies. Change requires tackling more than one lever.
- Emergent system behavior isn’t easy to predict. Structure generates behavior. However, even if a system’s structure it is clear, multiple modes of behavior may be possible, for example depending on whether tipping points are reached. Keith encourages students to have an explicit theory about what they think is happening, design a policy intervention in response, and then use the simulator to test their understanding.