Teaching R in the Undergraduate Ecology Classroom: Approaches, Lessons Learned, and Recommendations

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Learning ecology requires training in data management and analysis. 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 bachelor's degree and a required knowledge of R have increased over the past ten years. In this paper, we begin by presenting data from the last ten 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. We then discuss our experiences teaching undergraduates R in two advanced ecology classes using different approaches. One approach, in a course with a field laboratory, focused on collecting, cleaning, and preparing data for analysis. The other approach, in a course without a field laboratory, focused on analyzing existing datasets 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 commitment for course preparation; and there is a tradeoff between teaching R and teaching content. Determining how one's 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.




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