ropenscilabs / ropenscied Goto Github PK

I'm also very interested in being involved with this as it moves forward (thanks for starting it up!).

I work in applied linguistics. R is a part of three courses that I teach:

1. An undergraduate language assessment course. Students learn how to use R to summarize test results and carry out analyses of tests and their questions. The students are also introduced to the basics of rmarkdown. I would describe the use of R in this course as medium.
2. A graduate level introduction to research methods in second language research. This is new this fall. The challenge for me here will be learning more about how to incorporate qualitative data analysis into a workflow using R alongside of quantitative approaches. I know of RQDA.
3. A graduate level quantitative research methods course. R is used/taught heavily in this course. The challenge comes more in the balance of learning/teaching R and learning/teaching all of the course objectives. I'm attempting to address this challenge in part by introducing R at earlier stages in student coursework (see 1 and 2 above).

Unfortunately, I haven't taken the time yet to make any of my materials for these courses public (I plan to soon). I've been at under this, sort of, approach now for one academic year, and I am heading into my second.

I'm interested.

I've been working to get our Intro Bio labs using R for data analysis. See https://github.com/rachelss/BIO103R

I am trying to build on the above by teaching students to analyze ecological data in parallel to taking an Ecology class. See https://github.com/rachelss/BIO263_Fall18

I hope we'll begin to teach many of our classes using data now that all our majors have a base skill set in R.

I'm be really interested in participating if this initiative keeps going forward. The challenges mentioned in the posts (especially between balancing skills and domain content) really resonate with things I've encountered in my classes.

I'm teaching a mandatory recitation for an undergraduate biostatistics course next semester. This will be my third time teaching it. The first year, we used SPSS like in previous years. Then, I was able to convince the instructor to switch to R if I would stick around to teach the recitation. The first year using R went really well, I think, and we (me and another TA) learned a lot. This year I'm redesigning a bit to focus pretty exclusively on the Tidyverse. The only real hesitation before was that ggplot2 was more than most students needed for this course. But the different syntaxes used by different base R plots confused students, so I'm hoping it's worth the upfront investment into ggplot2, even if it seems like overkill, to make things less confusing to students by the end. I've never really taken a course that taught R, or really had any formal training about teaching R or any other programing language, so it's difficult for me to know how I'm doing except by getting student feedback. I'm hoping to get and give feedback on teaching materials and strategies!