For a quick overview, check out this poster I put together for the UT Tyler teaching symposium, highlighting my experiences implementing this new course:
While each bullet point below could certainly warrant a post all by itself, I'm going ahead and outlining everything while it's still fresh in my memory, laundry-list style:
General course description:
- Lecture met twice a week for an hour and a half on Tuesday/Thursday morning (three hours total per week)
- Lab met once a week for three hours on Thursday night.
- Eight students enrolled, all biology majors, mostly pre-professional.
- Assessment consisted of weekly homework submitted via GitHub for lab and Blackboard for lecture. Students also completed a class project for lecture by researching and presenting on a topic we didn't cover in class.
- Only pre-requisites were two semesters of introductory biology.
- I tried to adopt a lecture style that minimized actual lecturing (I averaged 20 slides for an hour and a half lecture). I implemented class discussions and think-pair-share type activities, including drawing a concept map at the end of semester to summarize.
- For lab, my students loved R, especially working in RStudio.
- I explored the use of analogies to explain complicated concepts in genomics and bioinformatics.
- I used signed pre- and post-class surveys and anonymous mid-semester evaluations to gauge how students felt about the class (this is mostly how I know things were working well!).
- Establishing the computational infrastructure remains challenging. I can't require my students to have their own (personal) machine for installing software. I have a computer lab for students to use during lecture and lab, but university policy constrains my ability to use these machines (e.g., I can't install software myself). I also had students log on to a remote HPC resource through TACC, but about half my students had problems accessing it.
- Continued from the last point, I had students use Cygwin to learn Unix/shell/bash commands, but the installation on the class computers made the path names ridiculously awful to navigate. My students agreed this was their least favorite part (which is a shame, since shell scripting is my personal workhorse for research).
- Students appreciated not having exams, but the workload (for them and for me grading) was a bit cumbersome (I had a lecture and lab to grade for each student almost every week). I will consider using alternative assignments (weekly online quizzes, and halving the number of lecture assignments) in the future.
With all of that in mind, I'm pretty happy with how the semester finished out, and am still excited to teach Bioinformatics for Research at the graduate level this fall.