Global Climate Models for The Classroom: Improving Science Education on Today’s Complex Socioscientific Issues

By Drew Bush and Renee Sieber

 Each week, we discussed how technology-based learning with a global climate model (GCM) impacted students. Most mornings, Drew also rode the bus to John Abbott College. Over the course of the winter term in 2014, he collaborated with a Geology instructor there to teach 39 students how to conduct research with an actual GCM from the United States National Aeronautics and Space Administration (NASA).

Many of the students were shocked by their findings. They had been taught how to design appropriate modeling experiments, run simulations, post-process data, conduct visual analyses and interpret results. One student reported dismay at changes to ice cover at the poles. Others calculated an alarming estimate of global sea-level rise. More than a few realized that a favorite animal, tree or vintage could suffer with climatic changes. These findings were made despite the fact that few of our students had ever worked with computer models beyond “toy” models used to teach basic physics or those generated through statistical programs/Microsoft Excel.

EdGCM component collage
The Educational Global Climate Model (EdGCM) enables students to learn about climate change through inquiry instruction with a real United States National Aeronautics and Space Administration (NASA) global climate model (GCM). It was the subject of interdisciplinary research in McGill University’s Department of Geography, School of Environment and Faculty of Education. (Image courtesy of The Educational Global Climate Modeling Project, Columbia University, NASA/GISS, New York, NY.)

A challenge of climate change is that it tends to be spatially and temporally distant. It is difficult for the majority of students to tangibly experience climate change[1] and most incorrectly associate weather events with it.[2] To compound the problem, climate change often is represented in politics and public discourse in conflicting manners. Even graduate students have trouble understanding the topic.[3] Research has shown that most educational models are based on the idea of a deficit, where students are considered empty buckets to be filled with more and more information.[4] Yet this instructional approach simply hardens positions on scientific issues that are politically controversial.

Our research reviewed educational theory and the literature on teaching science/climate change with science education technology to determine how best to overcome these obstacles. We found that instructional approaches that combine strongly guided student inquiry with scientific technology can impart deeper understandings and develop student higher order thinking abilities. Inquiry instruction emphasizes students posing their own research questions, evaluating evidence-based answers or explanations and communicating findings. What we still didn’t know after this review was what instructional approaches or technologies would prove most effective for climate change.

Drew’s doctoral work in the Department of Geography and McGill School of Environment examined the advantages and shortcomings of specific instructional approaches and scientific technologies for teaching science. Conducted in Dr. Sieber’s lab, the aim of this research was to determine an effective means for improving student comprehension of physical climate science and related policy. Our work also involved an interdisciplinary group of researchers located at NASA’s Goddard Institute for Space Studies (GISS) in New York, NY and McGill University’s Faculty of Education.

This research embraced the techniques of educational research to compare learning gains between a treatment group that worked with Columbia University-NASA GISS’s Educational Global Climate Model (EdGCM) and a control that listened to a lecture on GCMs and worked with climate education technologies suggested by the American Association of Geographers. These included the University Corporation for Atmospheric Research’s Very, Very Simple Climate Model, NASA GISS’s Surface Temperature Analysis Page and data/visualizations from sites like the National Snow and Ice Data Center.

Our hypothesis was that by working with the technology and processes of climate scientists, our treatment students would better understand climate science and related policy. To measure learning gains and analyze the impact of our otherwise identical curricula, we used pre/post diagnostic exams, exit interviews and the minute-by-minute analysis of 535 minutes of class and lab video footage—among other research instruments. This approach allowed deeper interrogation of the technologies used.

EdGCM is based on a real GISS research GCM. Dr. James Hansen first wrote about it in 1983 when he used it, GISS Model II, to make predictions of global change[5]. EdGCM itself consists of a suite of user interfaces that allows students to design experiments by manipulating inputs, running the model and post-processing and visualizing more than 80 different variables. Other graduate students in Dr. Sieber’s lab have designed newer generations of this technology that work online and possess more intuitive user interfaces.

The control students showed us the power of a well-organized and clear lecture. On the post exam, they out-scored treatment students on five multiple-choice questions that tested recall of facts about GCMs. Yet only those students who had worked with EdGCM appeared highly motivated in their work and demonstrated critical thinking about the work of climate scientists and the issue of climate change.

All but one of our 12 treatment student groups posed climate research questions that interrogated the spatial components of climate impacts or relationships between human actions today and regional/global conditions in possible future climates. As a whole, these students also demonstrated significantly greater learning gains on pre to post exams than those in a control.

The implications of this work are clear. More students understood the complex science of climate change when exposed to actual research processes. More importantly, these students better understood scientific research on the topic, a key tool of researchers (the GCM) and how their own behaviors and social interactions can contribute to solutions.

Renee Sieber is an Associate Professor in McGill University’s Department of Geography and School of Environment and Head of Geothink, an interdisciplinary research Partnership Grant funded by the Social Science and Humanities Research Council of Canada. Contact her @re_sieber

 Drew Bush is a doctoral student in McGill University’s Department of Geography and School of Environment. His doctoral work was supported through a Richard H. Tomlinson Fellowship in University Science Teaching and his efforts instructing graduate teaching workshops as a Tomlinson Project in University-Level Science Teaching Fellow. Contact him @drewfbush


[1]See Kearney, A. (1994). Understanding global change: A cognitive perspective on communicating through stories. Climatic Change, 27(4), 419–441.

[2]See Krosnick, J. A., Holbrook, A. L., Lowe, L., & Visser, P. S. (2006). The origins and consequences of democratic citizens’ policy agendas: A study of popular concern about global warming. Climatic Change, 77(1), 7–43 and Akerlof, K., Maibach, E. W., Fitzgerald, D., Cedeno, A. Y., & Neuman, A. (2013). Do people “personally experience” global warming, and if so how, and does it matter? Global Environmental Change, 23(1), 81-91.

[3]See Sterman, J. D. (2008). Risk communication on climate: Mental models and mass balance. Science, 322(5901), 532-533.

[4]See Cooper, C.B. (2011). Media literacy as a key strategy toward improving public acceptance of climate change science. BioScience, 61(3), 231–237 and Pidgeon, N. F., & Fischhoff, B. (2011). The role of social and decision sciences in communicating uncertain climate risks. Nature Climate Change, 1(1), 35–41.

[5] See Hansen, J., Russell, G., Rind, D., Stone, P., Lacis, A., Lebedeff, S., Ruedy R. & Travis, L. (1983). Efficient three-dimensional global models for climate studies: Models I and II. Monthly Weather Review, 111(4), 609-662.

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