Below, Prof. Michael Sipser describes various aspects of how he taught 18.404 Theory of Computation in Fall 2020, during the Covid-19 pandemic.
Michael Sipser: This subject explores the fundamental capabilities and limitations of computer algorithms, according to various computational models and measures.
Michael Sipser: I hope that students appreciate the theoretical depth and beauty of computation and that it is a vibrant area of ongoing research.
Michael Sipser: I try to focus on the big picture and the intuition. I give examples and specific cases which capture the essence of the material and let students see for themselves how to generalize these concepts.
Michael Sipser: Creativity is essential for doing research in this area and for solving the problem sets that I assign.
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Michael Sipser: Teaching remotely worked better that I originally thought it would. But it was an immense amount of work to prepare the presentations and slides. My effort to get at the bare essence of the material worked well in person and remotely. The hardest part to maintain remotely was the informal interaction with the students, especially because the class was large. To compensate, I built in time after every slide for answering questions that came in via “chat.”
Michael Sipser: I left it up to the students themselves to form communities. I offered them community-building resources such as the math-department’s Pset Partners tool that is excellent, as well as Piazza.
Michael Sipser: The mathematics community has a tradition of sharing materials so that we help each other. I get questions from everywhere in the world and I enjoy that.
Michael Sipser: Have fun with it and keep it interesting.
Michael Sipser: I feel lucky to teach this wonderful course to MIT’s amazing students. I appreciate your efforts and MIT’s commitment to disseminating knowledge.
The students' grades were based on the following assessment elements:
- 18.404J can be applied toward a Bachelor of Science in Mathematics, but is not required.
- 18.4041J can be applied toward a Doctorate in Mathematics, but is not required.
- 6.840J can be applied toward a graduate degree in Electrical Engineering and Computer Science, but is not required.
Every fall semester
Increasing in recent years, from about 120 to about 250 students.
Breakdown by Major
Approximately 40% EECS majors, 25% EECS graduate students, 20% math majors, 5% physics majors, and 10% others.
How Student Time Was Spent
During an average week, students were expected to spend 12 hours on the course, roughly divided as follows:
Met 2 times per week for 1.5 hours per session; 26 sessions total; mandatory attendance
In recitations, teaching assistants reviewed material covered in the lectures, guided students through practice problems, and answered questions.
Out of Class
Outside of class, students completed problem sets and studied for exams.