Herbert A. Simon Award for Teaching Excellence 2021
School of Computer Science, Carnegie Mellon University
Pittsburgh PA 15213-3891
(412)268-8525 . (412)268-5576 (fax)

Interaction and Suspense

David P. Woodruff

It is a tremendous honor to receive the Herbert A. Simon Award for teaching, and I want to thank the incredibly amazing students and teachers at Carnegie Mellon for shaping my teaching philosophy. I am fortunate enough to write this largely because of what they have taught me.

I teach two very different classes at CMU - a small Algorithms for Big Data class with about 20 students, and a large Algorithm Design and Analysis class with about 200 students, but the same principles apply to each: (1) always be patient and respectful to all students - each question of each student was either a question I had at some point or a question I should have had at some point, (2) prepare as much as possible - time your lectures, find ambiguities on your slides, try to predict any question a student might ask, watch previous lecture recordings, scrounge the web for related material, (3) remember, a class is like a free fall - it's not just lecture, recitation, and office hours, it's complete immersion; be a non-stop piazza-answering machine, and always provide emergency roadside assistance to anyone who needs it.

In terms of style, I try to make my lectures interactive and rival the suspense of a thriller novel. I ask multiple questions on each slide, and try to have the students tell me the next step in each of the mathematical arguments. A perfect lecture is one where the students are very engaged and I am just pressing the clicker and they are doing most of the talking. Every once in a while there is a step that is hard to predict, even after some thought, and that is when those 'a ha' moments come that you can feel shake through everyone in the room and remind yourself why you are teaching in the first place.

Another technique I like for increasing student engagement is to clearly convey proof intuition. A presentation technique I am fond of is providing a series of incorrect, natural approaches that one might try when first solving a problem. This allows me to relate to the student's thought process, and allows the student to better appreciate how a proof was conceived.

Let me give a shout out to Anupam Gupta and Danny Sleator for teaching me how to teach. Also, many thanks to all the wonderful TAs and especially the students I have interacted with at CMU - I hope you have learned as much from me as I have from you.

23 May 2021

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