Implementation of a Computational Component in an Introductory Climate Science Course

Teaching computation alongside traditional curriculum in scientific courses improves retention of class material and allows students to develop important applied skills relevant in other areas of their education. For non-major students who must take a climate science course for their general education requirement, there is considerable resistance to approaching quantitative aspects of this largely survey course. However, it is an important part of the student learning outcomes that students be able to work with data and understand quantitative measures like graphs, tables, and statistics. By developing these skills alongside the qualitative curriculum, the students will be required to think more holistically about the material presented.

This initiative will be tested in an introductory climate science course taught at Southwestern University, a small, private, liberal arts institution in Texas. The class fulfills a general education science requirement in addition to being part of the curriculum for the Physics and Environmental Studies Departments. The course is taken by students at all academic levels and from all different majors. The course is most popular among non-science students. The textbook will be Introduction to Modern Climate Change by Andrew Dessler. The course will meet three times per week and will be divided into two days of lecture and one day of computation. Each week’s computation activity will be closely tied to the lecture material.

Computational curriculum will begin at a basic level, with activities being tied to the material presented in the lecture portion of the course. As students abilities improve, more complexity will be added to computational activities. Some of the fundamentals which will be covered as part of this course will be: basic mathematical operations, importing large datasets, performing operations on vectors and arrays, graphical presentation of data, loops, conditional statements, and quality assurance of data. The computation portion of the climate science course will be based on the programming language “R”. R is freely available for download, which eliminates several logistical issues for the class like access to a computer lab, etc.