When I was in college, all my discussion sections had the same structure. The Teaching Assistant (TA) would give a short lecture that repeated the greatest hits of the main lecture and then do problems on the board from our last homework assignment, focusing on the ones we had screwed up the most. Sometimes there would be a few minutes at the end where he or she would ask us if we had any questions. None of this was particularly helpful, and if we had been given written solutions to the homework, section would have been even less helpful. I structured my sections this way when I was a TA in grad school, and as far as I can tell, most college sections (at least for science/math/social science classes) are run the same way today.
When we improve a system’s economic efficiency, we allow it to produce the same amount of output (or more) with fewer inputs. Economists like these kinds of improvements because they free up resources that can be then used to produce other goods and services, and in most markets, improving efficiency in production results in higher output and lower prices for everyone.
In addition to the undergraduate teaching I do in the economics department at Yale, I teach statistical methods in the RWJ Clinical Scholars Program. Starting at ground zero with an intensive 5 weeks of foundational probability and statistics over the summer, we gradually build up to some pretty fancy methods by the end of the following spring. My students are terrific–They are all physicians who want to know how to read and understand published research and analyze their own data. No one is there because they have to be there–everyone is invested. That makes my job a lot easier and a lot more fun!
When teaching a small (15-30 student) class, it’s easy to be interactive. My natural lecturing style is conversational, and I’m constantly asking students questions and breaking them into pairs or small groups to work through problems. I think a lot more learning happens when students actively engage with the material.
After 13 live sessions, 13 quizzes, 4 problem sets, many hours of video lectures, hundreds of textbook pages, two exams, one big empirical project, and now 14 blog posts, I can say with confidence that everyone involved with my online econometrics class learned a lot this term. Here are the highlights:
Last Wednesday was our last class meeting before the final exam, and I reserved most of our time to answer questions about any topics that have come up in the class. I asked them to send their questions the night before, and said that I would assume anyone that didn’t send questions had full command of the material and would help me answer everyone else’s questions during class. This incentive induced almost everyone to send questions before class.
I am a huge believer in peer-to-peer learning and I love interspersing my in-person classes with small group exercises. It’s a nice break from lecturing and allows the students to actively work with the concepts I’m teaching that day. I walk around the room during these exercises and try to unstick any groups that get stuck.
During the last month, my TA and I have created quizzes for all 13 modules in the class. Each quiz is made up of 10-15 multiple choice questions that test whether the student is absorbing the main points of the video lectures. The students get practice applying and combining the concepts with more difficult exercises in their homework. I think the quizzes have been successful, although with just 8 students in the class it’s hard to tell for sure.
We reached a big milestone Friday as my students read their first primary research articles and we discussed them during our live session. Coming into the course, most of my students knew that correlation doesn’t imply causation. For example, just because cities with more police tend to have higher crime rates doesn’t imply that hiring more police induces people to commit more crime. In a sense, econometrics is just a set of statistical methods for going beyond correlation and estimating actual causal effects.