rOpenSci Educators Collaborative: What Are The Challenges When Teaching Science With R?

Authors: Laura Ación, Mara Averick, Leonardo Collado-Torres, Auriel Fournier, Alison Presmanes Hill, Sean Kross, Lincoln Mullen

At the 5th annual rOpenSci unconference in May 2018, a group of scientists and educators shared their experiences, frustrations, failures, and successes teaching science with R. What came out of this discussion was a framework for rOpenSci Educators’ Collaborative: a community of practice for people interested and engaged in science education using R. This blog post is the first of a three-post series about education and R, written by this group of unconf18 participants.

Educators who teach science using R tend to face common pedagogical problems, regardless of their scientific domain. Yet instructors who teach with R often feel isolated at their institutions. They may be the only ones in their departments to teach using R. Even if there are others, the culture of collaboration around teaching is generally impoverished, unlike the rich culture of collaboration around research. In this three-part series of blog posts, participants at the rOpenSci 2018 unconf briefly survey the state of teaching science with R.

Read post 1 of 3 here:

The post contains a very precise description of the challenges I encounter each semester while teaching subjects such as basic statistics, econometrics and, recently, introduction to data science.

Given the limited time available in just one course, I came to the conclusion that striking a balance between the subject matter and R is very, very difficult in just one discipline, a specific discipline on the R language would be the ideal solution. Congratulations for the initiative, I’ll look forward to the next posts

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