Using Project EDDIE modules in Data Science for Life Sciences
About this Course
Data Science for Life Sciences
EDDIE Module(s) Adopted and/or Adapted
This hypoxia case study was implemented toward the end of the semester in my Data Analysis for Life Sciences course. As such, I wanted this to simultaneously be an in-depth exploration and a practice run for how the students were then shifted to their own semester-end projects. In addition to modifying the materials to run in an R programming environment, I split the material by ecological themes—Day 1: physical factors, Day 2: chemical factors—to encourage synthesis of concepts.
Relationship of EDDIE Module(s) to my Course
Implemented toward the end of the semester, students will be tackling most of the materials independently from the lecture slides with their peer groups in the form of in-class lab sessions. This environment promotes a lot of communication among the students.
In addition to switching the computer processes from Excel to R, I have rearranged the materials to be more modular. Students encounter the introduction and definitions on their own in pre-lecture assignments. After the in-class labs with the coding and calculations, students synthesize their findings in brief writing tasks to finish the week.
Student Handout for Day 1 activity (Acrobat (PDF) 271kB Jun1 22)
Student Handout for Day 2 activity (Acrobat (PDF) 328kB Jun1 22)
How did the activity go?
At this point in the semester, the students handled the R programming well and were able to debug their errors among their peer groups. However, these sophomores had little interest in connecting the data and evidence with their general knowledge of biology. Perhaps spending more time on introducing concepts and definitions (such as the location of the Chesapeake Bay) could prove fruitful.
Perhaps due to the bulk of math and programming exercises in my course, students struggle with reading assignments and connecting the ideas with the data visualizations that we build in class.
I am looking forward to running this case study again in the Fall semester where, by the time I submit these adapted materials, I will have reordered the examples and exercises so that:
- Day 1 (physical causes): students encounter the temperature data on their own and hopefully think about global warming
- Day 2 (chemical causes): students encounter the nitrates data on their own and hopefully think about usage of fertilizers