Teaching R in the undergraduate ecology classroom: approaches, lessons learned, and recommendations

Abstract

Ecology requires training in data management and analysis. In this paper, we present data from the last 10 years demonstrating the increase in the use of R, an open-source programming environment, in ecology and its prevalence as a required skill in job descriptions. Because of its transparent and flexible nature, R is increasingly used for data management and analysis in the field of ecology. Consequently, job postings targeting candidates with a bachelors degree and a required knowledge of R have increased over the past ten years. We discuss our experiences teaching undergraduates R in two advanced ecology classes using different approaches. One approach, in a course with a field lab, focused on collecting, cleaning, and preparing data for analysis. The other approach, in a course without a field lab, focused on analyzing existing data sets and applying the results to content discussed in the lecture portion of the course. Our experiences determined that each approach had strengths and weaknesses. We recommend that above all, instructors of ecology and related subjects should be encouraged to include R in their coursework. Furthermore, instructors should be aware of the following: learning R is a separate skill from learning statistics; writing R assignments is a significant time sink for course preparation; and, there is a tradeoff between teaching R and teaching content. Determining how ones course fits into the curriculum and identifying resources outside of the classroom for students continued practice will ensure that R training is successful and will extend beyond a one-semester course.