This material was originally developed as part of the Carleton College Teaching Activity Collection
through its collaboration with the SERC Pedagogic Service.

Circling Complexity: Abrupt Change in Climate & Human Networks

Trish Ferrett, Carleton College

The climate system is an angry beast and we are poking it with sticks!

-Dr. Wally Broecker

Through teaching about complex systems in a course on abrupt climate change, I have developed learning activities driven by three guiding ideas. First, I find it useful to have students encounter complex systems in more than one real-world context – and it is critical that one of these contexts relates to common student experience. Second, I find that a recursive approach – a strategy the circles over and again through layers of real data, theory, and essential concepts related to complex system behavior – can be effective in deepening understanding. Finally, I have played with assignments that ask students to integrate their understating through the use, creation, and exploration of analogies for complex systems across several contexts. This helps students, through a creative and fun process, to generalize behavior while exploring unique differences that depend heavily on context. I will talk a bit about each of these ideas after providing a little content for the course itself.

The course is a 200-level science-rich course for environmental studies majors. Using a data-rich and active-learning classroom approach coupled with term-long team projects, we tackle thorny questions that also baffle researchers. How fast can climate change, and why? What is the evidence and how strong or shaky is it? Is abrupt climate change in our future? How does past civilization "collapse" link to abrupt climate change? The course opens with Kolbert's Field Notes from a Catastrophe, anchoring students in today's issues of climate change with some captivating storytelling. We read and discuss a range of literature articles on climate change, along with Alley's book, Two-Mile Time Machine. We also take on Gladwell's Tipping Point for a context related to human social networks. We engage in short case studies on the Maya and Natufians related to abrupt climate change of different magnitudes. In addition, the course is largely driven by projects where diverse student teams, united by a common interest (water, natural resources, energy, indigenous cultures...), create a website that tells a story at the intersection of abrupt climate change and their shared interest. Each website is produced in connection to a partner organization chosen by students, so academic civic engagement is a key feature.

Multiple contexts. Students begin by playing the Tip-It game on the first day of class. I ask them to play the game and carefully record their observations of the systems. I argue that some "essential features" of complex systems are exemplified in the game. We make a class list of these features, an dthen revisit and revise it several times throughout the term. We next encounter abrupt change in climate systems, and then in human social networks. Our case studies on human civilization collapse raise yet another set of issues around abrupt change. On the team projects, students have their last deep learning experience about abrupt change. On the team projects, students have their last deep learning experience about abrupt change. Some of their most profound learning grows from thinking about how to connect the science of abrupt climate change to their topic, and how to educate the public to move from a paradigm of gradual to abrupt change. Finally, we explicitly contrast the behavior of simple linear systems with complex ones – often on a spontaneous basis as questions arise in class.

Recursive teaching and learning. The most recursive feature of the pedagogy is the approach to using historical climate data. We begin by looking at proxies of local and global temperature in the last 100 years. Then we go back several hundred years, several thousand, 10,000, 20,000, 1 million, and 2 million years. We also look into very deep time (several billion years) to explore earth's hothouse and icebox periods. Each time the time window opens further back in geological time, the data set also contains all prior data sets. We often have to either re-interpret the most recent data and/or revise our understanding in light of new data. In this sense, the "data game" we play all term is recursive. We also play the same game with theories for abrupt climate change on various time scales. There is a strong interplay as well between data and theory- a huge theme in the course. Finally, as noted above, we keep revisiting our list of "essential features of complex systems." These ideas eventually get incorporated into each website in a way that fits with the project context. Some teams decide to emphasize hysteresis or the role of noise in threshold crossing, while others focus more on feedbacks, tipping points, or emergent behavior.

Analogic and integrative assessments. This student work initially operates explicitly at the boundary between two contexts for abrupt change – at the interface between natural and human networks. While we are discussing the Alley and Gladwell books, I have students write a paper where they take concepts and terms in one kind of network, and make analogies to the other network – in an attempt to "learn something new about complex systems." A student might choose, for example, try to apply Gladwell's concept of "the connector" to thinking more carefully about the ocean's thermohaline circulation. My own scholarship in teaching and learning, through analysis of this student writing, has led to a taxonomy for integrative learning that has a developmental axis to it (ask me more about this at the workshop). I find that the direct, explicit approach to comparing two system types serves to deepen understanding about both commonalities and context-specific aspects of system behavior. It helps move students from abstract concepts to multiple and concrete examples of how these ideas play out in real systems. Finally, in the team project, students are asked to make analogies for key ideas about complex system behavior. I will never forget the day in class when one team proposed that we could think of stochastic resonance in the following way: as a team of trampoline jumpers, jumping up and down mostly in unison and to large heights in a periodic fashion – disturbed by 1 more "noise" jumper added enough in-phase amplitude to a periodic jumper to cross a threshold that flipped the periodic jumper entirely off the trampoline! "State flip induced by noise coupled to periodic processes," they cried.

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