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The materials in this course were developed through an NSF grant designed to improve how students learn about and interact with polar regions. The intent was to create materials to help students engage with polar data and researchers and learn more about how polar science issues affect people and animals
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Module 3 Sea Ice as an Indicator of Climate Change

Jonathan Cohen, Matthew Oliver, and Victoria Simons (University of Delaware)

Summary

This module focuses on the differences between the Arctic and Antarctic in terms of physical factors like sea ice cover. This is the first polar content-heavy module of the course, and it relies on skills built in the first two modules. It is intended to introduce students to how sea ice forms, and the rate at which sea ice cover is changing at the poles. Students will interact with current sea ice data, plot it, and draw their own conclusions about how sea ice cover has changed over the years in both the Arctic and Antarctic. They will read a news article related to sea ice levels, then pen a letter to the editor based on the data they plot.

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Learning Goals

  • Students will be able to list the important properties of water
  • Students will be able to describe how seawater and freshwater differ
  • Students will learn what sea ice is, how it forms, and why it is important
  • Students will be able to describe how sea ice is affected by factors like wind and currents, and how it changes across seasons and years
  • Students will gain an appreciation for how sea ice is talked about in the news
  • Students will compose a thoughtful letter-to-the-editor based on scientific data they find, analyze, and interpret

Context for Use

The content here is intended to span several 75-minute class periods, where students discuss a news article, have a lecture, complete a pair programming exercise with the aid of instructional videos, and conclude with an opportunity to write a response to the author of the news article read at the beginning of the unit.

If adapting this entire course, this is the first opportunity for students to really practice what they've learned in the previous two modules. They will need to use their narrative interpretation skills as well as their R plotting skills to visualize data and draw conclusions. It could be included as part of a different class to start a conversation about sea ice cover; however, it will need to be adapted if the previous two modules are not included.

Description and Teaching Materials

This module and the two following have a similar outline. Students should be given the news story ahead of time and should read it and fill out the Elements of a Story form prior to the first class of the module. The form should be submitted before class, and students should come to class ready to discuss the article.

The first part of class should be spent discussing students' thoughts on the article, and what they thought the heroes, villains, problems, and solutions were. The handout includes several questions on it which can guide how students should be thinking about the article and data as they move forward. Following this, a lecture can be given to introduce students to the key properties of sea ice. This can be done in the same class period or may be spaced out over several class periods to limit the time spent lecturing in any one class period. Additionally, the lecture can be removed entirely and replaced with another method of information dissemination, such as an in-class reading and discussion.

Example topics for teaching that sea ice is an indicator of climate change:

  • Latent and Sensible Heat of Seawater
  • Constituents of Seawater
  • Sea Ice
    • Types of ice and formation
    • Sea Ice as Habitat
    • Seasonal Changes in Sea Ice
    • Annual Changes in Sea Ice
    • Sea Ice as a climate indicator (trends vs cycles)
    • Climate Feedbacks with Sea Ice

This module contains two instructional videos, and it is intended that each video is allotted one class period for students to accomplish via pair programming. The instructor (and near-peer teaching assistants if available) circulate to help students as needed to make their code. If students do not complete their code in class it can be finished as homework, but encouraging students to complete this work as a pair is encouraged. Students will generate graphs in R, and these can be submitted at the beginning of the next class period for a few points, creating a low-impact formative assessment that encourages students to stay engaged in the class.

After the videos have finished and students have generated their graphs, the discussion can return to the article to see if students have different viewpoints after looking at the data themselves. This can occur at the end of the class period after watching the second R video or can happen the following class period. The questions on the handout can help facilitate this discussion, and students should now be able to answer all the questions on the sheet except for the last one which requires work outside of class.

Students next focus on finding more data they can analyze that is related to the news story. Students are encouraged to work in their pairs to do this, but can diverge if they choose. Finally, students individually pen a letter to the editor to respond thoughtfully to the news article. This letter should include graphs of the data covered in class and other data the student finds on their own. This serves as the summative assessment for the module, as the letter will show students' grasp of what the article says, what their data says, and demonstrate the students' ability to critically analyze and draw conclusions from both.

Teaching Notes and Tips

Students are likely to struggle with the heroes, villains, problems, and solutions of the article, so they will need help during the class discussion to ensure everyone understands. While it is best if the students can work through the details as a class, they may need some guiding questions from the instructor to help them reach the correct conclusions. One way to go about this is to first have students list off all the people and things discussed in the article, then categorize them into good, bad, or neutral as presented by the article.

Students may need assistance with accessing the data sets, as the way the website is arranged may change slightly over time. It is suggested that the instructor try to access the data a few days in advance so that any potential problems can be addressed. Additionally, should the websites be inaccessible on the day the students need to access them, it is a good idea to have downloaded copies of the data sets ready to distribute as a backup.

With the R code, if students follow along with the video, they should have little trouble. Where students may struggle is when asked to find their own data sets. This can be particularly daunting for students who have never had to seek out data before. These students may need extra attention and assistance to become accustomed to how to seek out new data sources. An alternative option is for the instructor to provide several suggested data sets for students to access and analyze, as this eliminates the need for students to search for new data but still requires them to choose a data set and work through it on their own.


Assessment

Students should turn in their Elements of a Story form before class, which can be graded. At the end of the module, students will generate a letter to the editor as well as R code with graphs, all of which can be submitted for a grade. The Elements of a Story form is a small formative assessment intended as homework to ensure the students read and understand the news article that is the focus of the unit.

As students work through the code for the two videos, they will generate several R plots. Having students submit these at the start of the next class provides further motivation to keep pace during class, and anything they do not finish in class they then finish at home.

The letter-to-the-editor (Example Rubric (Acrobat (PDF) 289kB Jan8 20)) is the product that tests understanding of both the news article and the data set analyzed. It goes a step further by having students bring in an additional data set to their discussion, ensuring that students are not just parroting back concepts learned in class but are actively applying them to something not directly worked through in class.

References and Resources

  • Morrissey et al. Intro to the Biology of Marine Life (Ch. 2, Ch. 14.0 and 14.1)
  • Mathiesen, K. "Why is Antarctic sea ice at record levels despite global warming?" The Guardian, October 9, 2014.
  • NOAA/NSIDC; Sea Ice Concentration and Sea Ice Index
    • Meier, W., F. Fetterer, M. Savoie, S. Mallory, R. Duerr, and J. Stroeve. 2013, updated 2015. NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 2. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: http://dx.doi.org/10.7265/N55M63M1.
    • Fetterer, F., K. Knowles, W. Meier, and M. Savoie. 2002, updated daily. Sea Ice Index, Version 1. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: http://dx.doi.org/10.7265/N5QJ7F7W.
  • R Core Team. 2017. R: A language and environment for statistical computing. Vienna, Austria. URL https://www.R-project.org/

R code files (for instructor reference only)

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