One of the things that we all hope for is that our students will make connections between the material they encounter in one course, and the things they learn about in another course. You shouldn't "forget" what you know about macroeconomics when you go to your econometrics class, etc. In other words, we hope that students will look for the "big picture" as they learn.
Admittedly, that's often easier said than done. When you're sitting in class listening to someone talking about a particular statistical test, it's hard to see how this might tie in with something that your micro. prof. was talking about last week.
Connecting the sots across different subjects in the one discipline is difficult enough, but it's even more difficult to do this across different disciplines while you're still learning the material.
Today, I gave my last undergraduate "statistical inference" class for the the term. It couldn't have ended on a better note. Here's why.
After the class, one of the students stopped to ask a question - not about today's material, but about a paper he'd been reading in the journal, Economic Modelling. The student had been writing an essay for an English course and had chosen a topic relating to the Greek financial crisis. The paper he'd been reading was an applied econometrics piece, and he realized that this all related to what we'd been doing in our introductory treatment of the linear regression model. His specific question was "what is a VAR model, and how does it relate to a simple regression model?"
A good question, of course, but what was even more rewarding for me was to see him putting the pieces of the puzzle together, by thinking across the different subjects that he's studying. Good job!
© 2013, David E. Giles