I teach social science methods, and students take my courses because it's required, and would celebrate if these courses were removed from the curriculum. I remember my struggles when I started learning
R, and thanks to the ever-increasing amount of teaching resources (yay R4DS, moderndive, etc.) and tips, am constantly updating and looking for ways to improve my instruction and student engagement. Unfortunately, I seem to have hit a road block this semester.
Most students seem to enjoy learning
ggplot2, and following sage advice from Hadley, Jenny, Mine, and others, I introduce
R through visualisation with real data (thanks to the
fivethirtyeight package). However, when I get to
dplyr, most of them seem to shut down; in fact, I had one student actually walk out of my class midway and never came back. The remaining students, save a couple of the most committed (thank goodness for them), look like they're at the dentist waiting for a wisdom tooth extraction without anaesthesia. I used to have students type
read_csv(file_path), learning about file paths and how to use a computer, but that created such an uproar that I now make them point-and-click Import Data in RStudio.
This is rather discouraging, and makes me question all the work I put in when I can have an easier time just teaching research design without code/math. I am constantly selling
R and statistical/computational thinking, linking these skills to getting a job and what I believe is more important: being a good citizen in a world of noisy data, but to no avail. To be sure, I get about two students in a class of 30 each semester super excited about
R and data science, but I see at best indifference, and at worst, anger in the rest.
Has anyone encountered this? Is there something about
dplyr that makes students balk? I don't get it...base
R is so much worse! How do you teach (or learn)
dplyr? Are there any Lego illustrations? I'd love to hear the community's thoughts.