18.404J | Fall 2020 | Undergraduate, Graduate

Theory of Computation

Instructor Insights

Instructor Insights

Below, Prof. Michael Sipser describes various aspects of how he taught 18.404 Theory of Computation in Fall 2020, during the Covid-19 pandemic.

OCW: For the uninitiated, what is computation theory? And how does it help us understand the world?

Michael Sipser: This subject explores the fundamental capabilities and limitations of computer algorithms, according to various computational models and measures.

"The mathematics community has a tradition of sharing materials so that we help each other."
— Prof. Michael Sipser

OCW: What big ideas do you hope students take from this course?

Michael Sipser: I hope that students appreciate the theoretical depth and beauty of computation and that it is a vibrant area of ongoing research.

OCW: How do you think about teaching complex topics like computation theory? How do you make content like this digestible and transferrable?

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.

OCW: What is the role of creativity in computation theory, and in the course?

Michael Sipser: Creativity is essential for doing research in this area and for solving the problem sets that I assign.

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OCW: What was it like teaching 18.404 remotely? Which of your teaching strategies translated well online? And which ones did you need to modify?

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.”

OCW: How did you develop a sense of community for graduate students while teaching remotely?

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.

OCW: Even before sharing your updated materials on OCW, you made your source files from Fall 2020 openly available to educators on your website. Tell us about your commitment to sharing open educational resources (OER). What motivates you to share?

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.

OCW: What advice do you have for other educators adapting your teaching materials?

Michael Sipser: Have fun with it and keep it interesting.

OCW: What would you like to add about teaching 18.404 that we haven’t yet addressed?

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.


Grade Breakdown

The students’ grades were based on the following assessment elements:

  • 35% Homework (6 problem sets)
  • 25% Quizzes
  • 15% Midterm exam
  • 25% Final exam

Curriculum Information


Requirements Satisfied


Every fall semester

Student Information


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.

Course Info

Learning Resource Types
Lecture Videos
Problem Sets
Lecture Notes
Instructor Insights