Teach the Earth > Affective Domain > Dilemmas about Teaching > Comfort in simplicity and discomfort in complexity

"I Want to Believe You": Is there comfort in simplicity and discomfort from complexity?


Eric Pyle, David McConnell

Professor Spurrier has prepared carefully for a presentation on paleoclimates, in an effort to have students learn about past climate changes. She presents information on current and historical measurements, tree ring data, ice core data, and ocean sediment data, going further into the past and demonstrating the inferences on what the climates were like. The students seem restless with this presentation, and finally one bright student raises his hand.

"Dr. Spurrier, I respect your work and want to believe you, but I am a little uncomfortable with the inferences you have presented. How can we really know what the conditions were like, when the data that you present is increasingly complex and more abstract? I mean, I can buy it when I see the first steps, even hold them in my hand, but there seems to be a lot built on more indirect information the further back in time you go. How does anyone know what the ratios of oxygen isotopes were hundreds of thousands of years ago? How can we assume that the ratios we see today bear any relationship to those in the past?"

How can one build student willingness to be a little more uncomfortable when presented with more abstract information?


Lensyl Urbano, LeeAnn Srogi

The problem:

  1. How students cope with/understand uncertainty.
  2. What students understand by scientific "proof" has both cognitive and affective aspects. Students are comfortable with faith and belief rather than reasoning from evidence. They think scientists "believe" things.
  3. Students live in the "now" (part of the developmental process to some degree). This is why data has no personal meaning.
  4. Students accept data from direct experience and are uncomfortable with proxy data, data collected by indirect methods.

The solutions:

  1. Spend a little time on statistics. Get students comfortable with the bell curve and Bayesian analysis in the context of the scientific process. It provides a good, visual way to express uncertainty and confidence. The idea of combining distributions together to increase or decrease uncertainty can be explained with examples. For example showing the overlap of multiple proxies such as Mauna Loa CO2 atmospheric concentrations and Antarctic ice core data to show how the two records overlap and one can be used to give confidence to the other when it is extended into the past.
  2. Have students do and/or design an experiment where they have to collect proxy or indirect data to answer a question (not necessarily related to geoscience) so that they can see that it is a valid strategy. Be sure to talk about the uncertainty.

Comfort in simplicity and discomfort in complexity  

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