Below is the last problem on a midterm for my graduate algorithms class. A few years ago, I started creating problems for this class that were based on (simplifications of) research problems. There’s a subset of the students that really like these problems and do well on them, but I worry sometimes that they hurt the students who are struggling in the class. I’m curious if others assign these types of problems for general graduate classes?
Filed under: Uncategorized | Tags: distributed algorithms, education, game theory, theory
Suresh Venkatasubramanian at geomblog blogs recent about active learning modules for graduate algorithms. I’ve frequently used active learning in undergraduate classes but somehow have found it less effective for graduate classes. However, just recently, I ran across a nice paper by Sivilotti and Pike that describes kinesthetic learning activities for a distributed algorithms class. The basic idea is to have each student simulate a processor that is running a distributed algorithm. Examples they discuss are non-deterministic sorting, parallel garbage collection, a stabilizing token ring, and stabilizing leader election. I also think the ideas could be applied to more advanced/theoretical distributed algorithms. A great thing about distributed computing is that it lends itself nicely to this sort of classroom activity.
I have not yet used these ideas in a graduate class. However, I frequently using active learning in undergrad classes and the students seem to appreciate it. I’ll probably try out some of the ideas in the next academic year. I’m teaching a game theory class in the spring where I can use these types of activities – even perhaps for “hard” problems like e.g rational secret sharing, auctions, etc.
When I first started as a professor, I felt that what students needed to do well in a class, above all else, was precise, error-free lectures, and lot’s of practice doing problems. Based on this ideas, I did most of my lectures from slides that I had very carefully prepared before hand, and gave the class lots and lots of problems to solve. This actually worked pretty well for a while – I got great feedback from students, was nominated for some teaching awards, and enjoyed the experience.
However, eventually I realized that my lectures were not as exciting as they could be. I read some articles on Tomorrows Professor listserv, that bemoaned the use of pre-prepared slides. They claimed that extensive use of slides makes lectures completely predictable and unresponsive. This semester, as an experiment, I stopped using slides, or even lecture notes of any kind. I memorize enough of the lecture so that I can be sure to use terminology that is reasonably close to the textbook and to the notes I’ve posted from previous years of the class.
How have things changed? I find teaching a more exciting and sometimes scary activity. Also, it’s easier for me to respond to feedback from the class as a whole about e.g. whether it’s worthwhile to go over an example of a particular concept. When a student asks an interesting question, I definitely spend more time than I used to on exploring the answer in depth. For me, at least, the lectures are a lot more fun and challenging. From the feedback I’m getting from students so far, they also seem to be more engaged. Do I make more mistakes in lecture? Definitely. However, I feel that I’m slowly getting better at checking things on the fly and am making fewer mistakes now than when I started this.
How has this changed my teaching philosophy? I realize now that a big part of education is inspiration, motivation, and a kind of educational “entertainment”. I also realize that it’s just much more engrossing and memorable to watch someone walk carefully across a rope in the air, than to trudge across a line on the floor that was drawn before the performance even began!
