By Lisa Lendway (Macalester College)
I have been gardening for nearly twenty years and teaching data science for three. I realized that I could combine the two by collecting data from the garden and using it in the introductory data science course I teach. The R-based course has no prerequisites and attracts a variety of students, from those who have never coded before and fear it to experienced statistics and computer science majors. Topics include data visualization and wrangling, mapping, animation and interactivity, and importing data techniques. My ultimate goal is to help students learn to use data to tell a story and make decisions.
The garden data is used in two ways: to reduce cognitive load when introducing new concepts and functions and to focus on details of a graph via a "Perfect Garden Graph" assignment. There is only so much we can hold in our working memories, and by using the garden data early and often, it becomes part of the students’ long-term memories. So, when I use it to introduce new concepts and functions, students do not also have to keep new data in their working memory, thereby reducing cognitive load. After practicing the new functions with the garden data, where those functions then become part of long-term memory, they move on to using the functions with other data. The in-depth graphing assignment, aptly named the "Perfect Garden Graph" assignment, has students working on the same graph, using the garden data, over the entire semester. Because they are acquainted and comfortable with the data early on, they only need a couple weeks to settle in on their graph. Then they have time to work on the details that can be easily forgotten in assignments where they produce many graphs, including color schemes, grid line choices, writing informative titles, calling out special cases, and more.
I have made the data available in an R package. The GitHub repo is here: https://github.com/llendway/gardenR. Some examples of where I use the data can be seen here: https://ggplot-dplyr-intro.netlify.app/#lisas-garden-data.