Using Project EDDIE modules in Invertebrate Biology
About this Course
Invertebrate Biology
EDDIE Module Developed
Phenology is a broadly accessible topic for students with clear relevance for understanding and predicting the effects of climate change; consequently, it provides strong motivation for students to develop data analysis skills. Using data from the National Phenology Network, students are able to make decisions about how to use simple tools like scatterplots and linear regressions to predict which species are likely to be impacted by climate change. They must wrestle with questions about data reliability and confidence in their answers.
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Relationship of EDDIE Module(s) to my Course
I have used this module in two different settings. I have used it twice, as described, in a 200-level Invertebrate Biology course with about 20 students. I use the module pretty early on in the course to review and develop quantitative skills for the students, and to introduce the importance of phenology. It's helpful for students to make connections about how dramatically temperature and climate can influence invertebrate life cycles. The activity takes place over 2 class periods, including one longer lab period.
I also used this module in a mathematical biology seminar. This class meets once a week in the evenings for 75 minutes and is taught by a rotating cycle of professors. Students in this class are either biology majors or math majors, and they often have an interest in biological modeling. I planned to meet with this group of about 30 students twice, but Covid 19 prevented the second meeting. I assigned the pre-phenology handout and introduced students to the context of phenology through the PowerPoint.
Teaching Details
What key suggestions would you give to a colleague before they used the activity in their teaching?
I typically have students complete the pre-activity materials prior to class the first day, introduce the phenomenon of a phenological mismatch with the PowerPoint, and then give students time to work through the activities in Activities A and B with periodic whole-class check-ins. Then students completed Activity C for homework, and we followed up during the following class session. In a small group like this, I enjoy having students present their findings on the white board. Then we look for patterns and surprises in the data. This activity provided an experiential foundation for reading and discussing some research papers on phenology. I suggest reading Kudo and Cooper 2019 before assigning the module, and practicing with the data.
How did you address challenges in teaching with the module?
One of the main challenges is that the data are "messy." We find the expected patterns only in subsets of the data. Also, for Activity C, there are many species for which data are very limited. I encourage students to think of this activity as an opportunity to explore real data and to think critically about the choices we have to make when we analyze data.
Student Outcomes
After completing the EDDIE module, students typically have a lot of uncertainty about their ability to make claims with phenology data. In many cases, limited data are available for species of interest, and they have seen how looking at different subsets of the dataset can change the interpretations they might make. They are, however, much more familiar with the kinds of data and analyses that can be used to make claims about phenology, and they have thought through and tested a number of predictions. This puts them in a good position to critically read and discuss primary literature about phenology. We typically follow the module by returning to the Corydalis ambigua story, reading and discussing Kudo and Cooper's (2019) findings that the mismatch between flowering time and the emergence of bumblebees explains a lot of the variation in seed set. Students learn a specific case where bumblebee phenology really does matter, some skepticism about making general conclusions, even from big datasets, and some tools to help them continue to explore data to answer questions about phenology. They still need to work on precision when talking about data.
Students were able to work with simple data, and to make choices about how to analyze more complicated data sets. They learned some very basic data cleaning steps.