Teach Better

Grade inflation at Yale is a sensitive topic–The administration doesn’t even like to call the issue grade inflation but instead refers to the problem as grade compression. The feeling is not that grades are (necessarily) too high, but that with so many A’s and A-‘a being handed out, it’s very hard to distinguish the good students and the great students. Is this really true? And is grade inflation itself a real problem? And if there is a problem with grade distributions, how should we fix it? I don’t have answers, but I do have opinions.

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With just a few exceptions, no one likes exams. Students don’t like the stress of taking the exams, instructors have to write the exams, and someone usually has to grade them. In-class exams don’t give enough time for testing very much material, and if the test is too long, it punishes students who know their stuff but are just a little slow. Take-home exams can cover more content, but it can be very tempting for students to cheat by getting help from friends or the Internet. Unfortunately, we need objective assessments of how much each student has mastered the course material, and right now exams are the best tool we have.

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MOOC’s are Massive Open Online Courses and they are what everyone in higher education is talking about. These classes are usually free, have huge enrollments, and per student are pretty cheap to run relative to a typical college class. The quality can be decent and MOOC’s open up access to higher education to literally billions of people around the world. MOOC’s also have the potential to decrease the cost of education for the millions of people that would normally attend a traditional in person college.

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At Yale, economics majors are required to take two “senior seminars” before they graduate. These classes usually have 10-20 students and revolve around reading and discussing contemporary research in a specific area. After three years of mostly big lecture classes on theory and methods, seniors finally get a chance to apply what they’ve learned to a substantive topic.¹ I just finished my fourth year of teaching two of these seminars, and while that might not seem like very long, I have learned a lot about what works and what doesn’t work.

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The big lecture is an institution in institutions of higher learning. The professor stands at the front of a hall full of students and talks. Sometimes he or she uses slides and sometimes he or she writes on a board. And sometimes, he or she is informative and engaging, but it’s almost always a pretty one way affair with occasional questions posed to the class.¹ The experience for students is a lot like watching a good documentary. And that’s the best case scenario. The vast majority of the time, students sit back and absorb the flow or just check out. They don’t get their questions answered or engage constructively with the material. The average professor talks at their students for an hour and a half twice a week and it’s more like a late night infomercial than a documentary.

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Every spring university departments match their faculty to the courses that will be taught the next year. Often, professors are assigned to courses they’ve never taught before. This is almost always the case for new assistant professors who haven’t really taught anything before. In the best case scenario, whoever taught the class the last time around has lunch with the new instructor, passes on a few pearls of wisdom, and hands over a subset of their course materials. I’ve personally benefited immensely from this generosity since it’s much easier to prepare a course when starting with a stack of slides, problem sets, and old exams. It’s also quite common to have to start from scratch. But there is a better way.

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According to the Internet, Chris Welty is now a research scientist at IBM’s TJ Watson Research Center in upstate New York. He works on knowledge representation and the semantic web and was one of the developers behind Watson, the computer program that kicked ass on Jeopardy! He also taught Intro to Artificial Intelligence at Rensselaer in the late 1980’s. As far as I know, he is alive and well. But life comes and goes and I really like the idea of writing this while he is still around to read it. You don’t always get that chance.

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MOOC is an acroynm for Massive Open Online Course. It’s a trendy name for packing up a course’s content (video lectures, problem sets, exams, a mechanism for peer interactions, etc.) and making it available to a large number of students over the internet without requiring significant live instructor input. It’s that last part that allows the system to scale and separates the idea from simple distance learning or a traditional online course.

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When most people think of labs, they imagine scientists in white coats staring into microscopes, carrying around beakers of bubbling chemicals, and holding test tubes over Bunsen burners. In social science, the reality is much more mundane. It’s usually just a room full of computers with software that may or may not be useful and may or may not be up to date. Even less compelling are the labs associated with statistical methods classes. The last couple years my own classes have been the worst case scenario–I just get up and lecture about how my students should use some particular piece of software to apply the methods we’ve been learning in the “lecture” part of the class. It doesn’t have to be this way.

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