SISL > 2012 Sustainability in Math Workshop > Activities > Arctic Sea Ice Extent

Arctic Sea Ice Extent

This page authored by Wm C Bauldry, Appalachian State University
Author Profile

This activity was selected for the On the Cutting Edge Reviewed Teaching Collection

This activity has received positive reviews in a peer review process involving five review categories. The five categories included in the process are

  • Scientific Accuracy
  • Alignment of Learning Goals, Activities, and Assessments
  • Pedagogic Effectiveness
  • Robustness (usability and dependability of all components)
  • Completeness of the ActivitySheet web page

For more information about the peer review process itself, please see http://serc.carleton.edu/NAGTWorkshops/review.html.


This page first made public: Apr 17, 2013

Summary

Students use the Arctic Sea Extent (total area) data from 1979 to the present to predict the trend in area for the next several years. Data is from the National Snow and Ice Data Center.

Learning Goals

  • Students investigate the disappearance of Arctic Sea Ice and have an opportunity to research effects.
  • Critical thinking and using a linear regression to discover a trend in nonlinear data.

Context for Use

This project can be used in courses in which linear trend lines have been introduced. Access to the internet for background on Arctic Sea Ice is useful.

Description and Teaching Materials

Student teams investigate Arctic Sea Ice by analyzing actual data and making predictions. A worthwhile extension is to predict the first year that the Arctic Ocean will be ice free.

The Arctic Sea Ice Project (Acrobat (PDF) 752kB Mar17 13)

The data and sources: Data Spreadsheet and LaTeX source file (Zip Archive 3.1MB Mar17 13)



Teaching Notes and Tips

An introduction to linear fits should have been completed. Connect the slope of the linear fit to the "trend" of the data.

Assessment

- Assess the correctness of the linear fit
- Assess the critical thinking displayed with the analysis of the trend.

References and Resources

National Snow and Ice Data Center