Using Project EDDIE modules in Introduction To Biology Lab
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HideEDDIE Module(s) Adopted and/or Adapted
I teach an introductory biology laboratory course at a technological school with many non-major students. As the biological sciences become more interdisciplinary and data-intensive, collaboration between biologists and scientists in other disciplines (such as computer scientists) will be vital to ensure transformative biological discoveries in the coming years. I offer two different laboratory courses. The first lab is a fully computational data lab designed for non-biology majors. We train students to take their technical skills in their given discipline (computer science, physics, or mathematics) and prepare them for meaningful collaborations with biologists. Alternatively, we designed a lab for biology students to ensure students gain the hands-on and computational skills needed to succeed as a biologist. I did one Project Eddie Module in both classes but ran each section differently depending on the skills and experiences of the students. In the computational lab, we used R and Rstudio to analyze data, while in the second lab section we used Microsoft Excel. By completing this module, students gained a thorough understanding of climate change science and the way humans have impacted Earth's climate.
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Relationship of EDDIE Module(s) to my Course
This introductory lab covers three main themes of biology: Evolution, Molecular Biology, and Ecology. The climate change module complements other labs in the Ecology section of the course.
Teaching Details
I taught this module during one 3-hour lab period. Since many of my students were computer science, math, or physics majors, special emphasis was put on collaboration between data scientists and biologists. We first viewed a YouTube video from Janet George featured on Girl Geek. Janet is a Data Scientist at Western Digital. This lecture introduces the path Janet took from a computer scientist to climate change researcher. My goal was to introduce students to a professional who has made an impact on climate research with a similar academic background of many of my students (e.g., computer science).
Due to the time it took for the opening discussion, I chose to only use parts A and B of the activity. Throughout the video and after the lab, I created discussion prompts for students on a live Google Doc (see associated file). After the lab I asked students to respond to one final question based on the lab: "Look at your graphs and timelines. When did we have enough evidence that climate warming was occurring? When "should we have known?" When should we have started to do something about climate change?" I like this question because it makes students analyze multiple graphs and come up with a numeric answer (year) based on their own analysis.
Adaption Materials
Wet-lab Syllabus (Acrobat (PDF) 1.1MB Apr26 22)
Discussion Topics (Microsoft Word 2007 (.docx) 14kB Apr26 22)
How did the activity go?
Students in both my sections did well analyzing the data and creating figures. Next time, I hope to do a better job explaining what a climate anomaly is, and what the temperature data means.
Students came away with the fact that we should have started to do something about climate change over 40 years ago. Climate change is something these students have grown up hearing about, but I don't think many have actually crunched the numbers themselves. This was a great opportunity for students to look at the severity of the climate crisis in a tangible, quantifiable way.
Future Use
I plan on doing this activity again. There are a few overarching things I'd like to change or improve on in the future.
First, I want to do a better job explaining what a climate anomaly is. Perhaps I will add additional slides into the PowerPoint lecture for clarification. Along the same lines, I think it would be worthwhile to explain where / how global temperature data sets are created (other members of the FMN came up with this idea and I think it is great!).
Next, I'd like to give students the opportunity to discover how temperature trends vary seasonally. The temperature data set is already organized into monthly and seasonal data. Investigating whether winters are warming faster than other seasons may be useful. For example, we could highlight the how important wintertime activities like skiing and ice fishing may change in the future with climate warming. This may also help students connect to climate change more personally.
Finally, I'd like to find a way to end the lab period on a positive note. Some students are quite disappointed when they realize how clear the climate patterns were 40 years ago, but we have made relatively little progress toward finding a solution. Finding an activity or video highlighting climate change solutions or progress, especially from a data scientists' perspective may prove to be a worthwhile concluding exercise.