Promising Pedagogical Approaches to Teaching Complex Systems
We are not aware of much research to substantiate specific best practices in teaching complex systems. This is a new field which requires ongoing collaboration between psychologists, cognitive scientists, educational researchers and practitioners, and geoscientists to derive definitive best practices. Much of this conference has focused on use of models, simulations, and visualizations as powerful tools to help students understand systems and properties of complex systems. It is important to realize that these do not stand by themselves but must be embedded in a viable pedagogical strategy that will support and demand thinking and sense-making from the students. This document summarizes much of what we know and have discussed on this topic during the 2010 workshop on Developing Student Understanding on Complex Systems in the Geosciences.
Some Challenges Inherent in Teaching about Complex Systems
Workshop participants identified the following key challenges they have experienced in teaching students about complex systems:
- Choosing where to begin. Do you start with the general characteristics of complex systems, before tackling specific examples? Or do you begin with a specific example, and use it to illustrate general characteristics? At what point do you define vocabulary terms, many of which will be unfamiliar?
- Asking students to deal with space and time scales beyond human experience.
- Complex causality (characterized by strongly interdependent variables, nonlinear interactions, and feedback mechanisms) does not mesh with cause–>effect understanding. Therefore, reductionist pedagogies – looking for cause and effect relationships – are generally not appropriate (Herbert, 2006). Breaking out of linear thinking patterns can be difficult for both students and instructors.
- Getting students to overcome the tendency to focus on "average" properties of a system. The non-Gaussian output distribution of complex systems makes average properties less likely than we are used to. Moreover, complex systems are rarely in equilibrium, so average properties may be even less applicable.
- Studying complex systems often requires an interdisciplinary approach.
- Biological evolutionary theory dominates as the only systematic mechanism for evolutionary change; self-organized criticality and emergence are unfamiliar concepts.
Effective Strategies (and Related Tools)
Workshop participants identified the following pedagogical approaches as being effective, in their experience. These methods are by no means mutually exclusive; on the contrary, they may be most effective when used together.
Using Computer Modeling to Teach Complex Systems
Systems modeling software can be used very effectively, in combination with inquiry-based learning, to help students explore the characteristics of complex systems.
Combining an Inquiry-Based Approach with Multiple Representations of Complex Systems
Inquiry-based approaches allow you to engage students in exploring real world problems.
Using a Role-Playing Exercise to Teach Complex Systems
Role-playing exercises can be particularly effective when you want students to explore interdisciplinary aspects (scientific, economic, political) of societal issues related to complex systems. For example, Jimm Myers and Greg Marfleet have designed a role-playing exercise in coupled complex natural and human systems for a pair of linked courses: a geoscience course and a political science or public policy course.
Other Effective Pedagogies
- Teaching with Visualizations can help students "observe" processes that they cannot take in directly, because of the spatial or temporal scales involved. In particular:
- GIS is a key tool for finding patterns, particularly through analyzing large data bases visually and statistically. Learn more about Teaching with GIS in the Geosciences.
- Google Earth is a valuable tool for increasing spatial skills, and can be a foundation for GIS. Learn more about Teaching with Google Earth.
- Teaching with Data allows students to explore complexity, with your guidance. More specifically:
- If you'd like students to work directly with multiple data sets, you might use a jigsaw approach. In a jigsaw, each student develops some expertise with one data set, then teaches a few classmates about it (and learns about related data sets from those classmates).
- Genomic and metagenomic data sets (DNA/RNA data) collected in the environment are a fundamental geoscience tool.
- Using the Field as Laboratory: geoscience field labs are unusually tactile and bring us into contact with real, messy (in all senses of that word) problems. For instance, as instructors we may start out with a focus on the lithology at an outcrop, but soon aspects of weathering enter the conversation and the physical "lithosphere" becomes linked to the atmosphere and biosphere. Thus the field can provide great opportunities for discussion of complex systems.
- Explicitly mimicking the Process of Science in instruction both to leverage what we know and to develop accurate understanding of what science is and how it is done.
- Using Web 2.0 and virtual learning environments, such as Online Games, to create accessible opportunities for students to construct, deconstruct, and understand complex systems
- Teaching metacognitive strategies, helping students to become aware of the learning challenges inherent in complex systems (by pointing out the difficulties directly).
- Addressing misconceptions directly. Misconceptions interfere with students' abilities to develop accurate understanding of new materials and ideas.
A Call to Action
While the approaches described above have worked well for individual workshop participants, there has been little research we know of delving into the question of how best to teach complex systems thinking. We need to clarify essential concepts to be learned, identify particular student difficulties, and test various strategies to see which are most effective in addressing learning challenges.