Using Project EDDIE modules in Freshwater Biology
About this Course
Freshwater Biology
EDDIE Module Developed
Determining the sources, temporal dynamics, and spatial differences in stream source water is a valuable exercise for general environmental science, geology, or biology students or students that are focusing on a water resource/aquatic ecology careers. This module helps students get exposed to a variety of streams outside of their local biome, hydrographs, working with R, and thinking about data!
Jump to: Course Context | Teaching Details | Student Outcomes
Relationship of EDDIE Module(s) to my Course
This module worked quite well in my Freshwater Biology course which is an upper level biology course. Most of the students in the course did not have an R background or have interest in future careers in limnology. This module fit perfectly into the second half of the course that focuses on flowing waters. We start by calculating stream discharge using example data in the lab and then go out to the field calculate stream discharge in a couple different ways. This fits into that lesson perfectly by expanding out to use some of the concepts we look at locally and one time point to a macrosystems scale.
Teaching Details
What key suggestions would you give to a colleague before they used the activity in their teaching?
Preparation in R is good - especially if you do not regularly use or teach it. Running through the modules using the computers the students will be using - if they are using their own computers, be familiar with installing R/R Studio on both Windows and Mac OS. Also, look for places in the module to connect students to each other and back to a discussion of the material that they are finding.
How did you address challenges in teaching with the module?
The module ran quite well in the class. The students, even inexperienced with R, were able to run through the code well. Some common problems include when the students open data files in any program - often date formats are automatically converted and graphs are no longer visible because of non-recognizable date/time formats when the data file is input into R. Several students also had to rerun, redownload files, or had R hangups - the main issue was impatience with R or their computers. Helping them redownload files or rerun code in order was important to making the module go smoothly.
Student Outcomes
Looking at data that has high frequency helped the students compare the measurements they made in the field at one location and one point in time to much more variability that occurred over time. This module also stimulated organic discussion between groups that looked at different locations and why they were seeing dramatically different results. This module better reinforced quantitative reasoning concepts in hydrology that I have in my class anyway and better prepared them for exam questions about drawing a hydrograph in different scenarios (urban vs. forested streams), different locations (desert vs. temperate forests), and different temporal scales (one rainstorm vs. one season vs. one year).
Working with real data at this large spatial and temporal scale made the students reflect on their location and how it might differ from many other locations around the country. The students were appreciative of getting exposed to R as a tool for working with data.