Using Project EDDIE modules in Limnology
About this Course
EDDIE Module(s) Adopted and/or Adapted
This module ran smoothly and tied into the curriculum well. Students commented that they enjoyed the module and had fun. The annotation of the R code was excellent, clear, and easy to use. Using this module to explore biodiversity indices after teaching phytoplankton and zooplankton ecology was a nice follow-up.
Relationship of EDDIE Module(s) to my Course
This module worked very well with the overall course curriculum. My Limnology course is set up over three modules (physical, chemical, and biological limnology), with a strong quantitative focus. The last module covers phytoplankton and zooplankton community ecology, so exploring biodiversity indices was a great way to wrap up and take a deeper dive into community ecology. The course focuses on lakes and ponds, so this module was slightly off topic in that it focuses on wetlands, but it wasn't difficult to tie in. I taught this EDDIE module at the end of the semester. Because of this, the deliverables were graded as "low stakes" and optional as a replacement for extra credit. However, students were made aware that the information would be covered in a final exam. Overall students found the material and activities engaging, regardless of whether they chose to use it as a graded assignment.
What key suggestions would you give to a colleague before they used the activity in their teaching?
Preparation in R before teaching this lab is important. We had spent lots of time throughout the semester learning R tidyverse basics, so students were well prepared to build on their R toolbox with more advanced commands they had not encountered before. Getting familiar with tidyverse syntax before the lab session is key, and I think it would have been more challenging if we had run this earlier in the semester without as much R practice. Having at least two hours to run this lab is necessary.
How did you address challenges in teaching with the module?
This EDDIE module ran very smoothly. The only challenge was that is was taught at the end of the semester. So, being QR "heavy," the grading for these activities was made low stakes to replace existing grades as extra credit. Students were not required to complete the activities, but they knew they had to know the material for the final exam. The majority of students did complete the work.
It was apparent that this module helped students exercise and further develop their quantitative reasoning skills. Class discussions of biodiversity indices interpretations, and using relative abundance values compared with raw count data helped in the development of these skills. Their exam question based on this module focused on interpretation of indices, and overall they demonstrated a strong understanding of the concepts covered in the module.
Students enjoyed the ease, clarity, and annotation of the R code. After the module, they commented on how fun it was. A couple students with more advanced R experience commented that they would have liked the opportunity to write more of the code themselves rather than having it mostly provided.