This is an opinionated post based on how I teach my undergraduate econometrics course. It will not be for everybody. The title applies mostly to anyone who wants to do data science or econometrics with R. This is the second time I have taught this course with R, and I have changed it around in many ways that I think optimize the process for students. In this post, I’ll cover just two major changes:
This Fall semester, I have made dedicated websites for all of my courses at Hood College that host nearly all the course content. You can see them all here. My interest was sparked when I saw Andrew Heiss’ amazing course websites.
Until this point, all of my course content has lived on Blackboard for my students, though I have also tried to post syllabi and lecture slides (if not additional resources) on my personal website over the past few years.
This summer, I am overhauling my econometrics class in many ways, in part because I was pleased to recieve a teaching grant from my college to make more R resources for my econometrics class. Last Fall was the first time I had taught it using R, and I’ve learned a ton since then. Expect a flurry of posts in the coming weeks more on those topics.
This post, however, explores some of the trends that I have been thinking about in teaching econometrics, and something monotonous that I have been struggling with that encapsulates the tension in these trends: what to name my course.
With the new school year in full swing, I have redesigned my personal website, and plan to make occasional posts on the tools I use in my research and teaching. Over the summer, I made the full conversion to using R, R Markdown, and Github for nearly everything I do in my professional life (including managing my website with Hugo/Academic).
This semester, I am teaching econometrics to my students using R for the first time, and optionally nudging them to use R Markdown for their homeworks and paper assignment.