Incorporating Generative AI as a Data Analysis Partner in the Meteorology Classroom

Graduates from undergraduate and graduate meteorology, climate, and environmental science programs entering private-sector and government jobs in the environmental monitoring, compliance, and analysis job market must have data analysis and visualization skills. A recent analysis of employers in the Environmental Science and Technology Sector indicated that one of the most sought-after skills is in data analysis and visualization, predominantly using Excel and Powerpoint or programming languages such as Python and R. The field of data analysis and visualization is experiencing a rapid shift towards using generative AI to increase efficiency in data analysis and improve data communication and storytelling. In response to this change, we adapted several data analysis exercises embedded in a upper-level undergraduate, flipped-classroom style course on Climate and Climate Change from utilizing spreadsheet type programs like Excel to working with a generative AI platform like ChatGPT as a partner in developing data-analysis code in Python. This shift not only meets the changing demand in private sector jobs but also enhances our meteorology and climate students' Python programming skills by providing real-world examples while asking them to engage deeply in the process of data analysis. Much like the benefits provided to students learning a programming skill utilizing paired-programming, it is anticipated that incorporating generative AI as a partner in code development can lower barriers for those learning coding for the first time and provide more opportunities to rapidly develop confidence in their data analysis skills. In addition, this classroom innovation is designed to encourage students to think critically about their data analysis and visualization goals and tools, assessing whether or not they understand the resulting analysis and if the analysis provides them insight to the research question posed. The ability to question and critique the process and products of data analysis as generative AI becomes more embedded in meteorological and environmental work is a critical skill for our meteorology, climate and environmental students.