Chancellor Eric Grimson engages novices in learning computer science, opening the field to everyone and empowering learners to cultivate their curiosity.
Eric Grimson is MIT’s chancellor for academic advancement and interim vice president for Open Learning; he’s also a longstanding professor of computer science and medical engineering. In this episode, Prof. Grimson shares his thoughts on in-person and online education. We learn that he rehearses each lecture one, two, or even three times before coming to the classroom, and that he often pauses in his speech when lecturing to avoid distracting his students with “um”s and “ah”s and similar disfluencies. But though some of the techniques he describes might seem to reflect a view of teaching as performance, Grimson firmly believes that education should be a dialogue rather than a monologue—that students should be engaged as partners in the exploration of the material, even in an introductory-level class. “Anybody with enough curiosity ought to be able to explore a field,” he says, “and we ought to be able to teach at a level that opens it up to them.” The same conviction underlies his commitment to sharing his expertise online, whether by publishing his course materials on MIT OpenCourseWare or through purpose-built MOOCs on MITx. [Warning: this episode also includes numerous bad jokes!]
The OCW Educator Portal
6.0001 Introduction to Computer Science and Programming in Python on OCW
6.0002 Introduction To Computational Thinking And Data Science on OCW
Professor Grimson’s faculty page
Music in this episode by Blue Dot Sessions
Connect with Us
If you have a suggestion for a new episode or have used OCW to change your life or those of others, tell us your story. We’d love to hear from you!
Call us @ 617-715-2517
On our site
Subscribe to the free monthly "MIT OpenCourseWare Update" e-newsletter.
If you like Chalk Radio and OpenCourseware, donate to help keep these programs going!
Sarah Hansen, host and producer
Brett Paci, producer
Dave Lishansky, producer
Show notes by Peter Chipman
[MUSIC PLAYING] ERIC GRIMSON: There are tons of talented people around the world who will never have the good fortune to be able to come to MIT, because we're a small place, but who are perfectly capable of handling MIT-quality, MIT-hard material.
SARAH HANSEN: Today on Chalk Radio, making sense of computer programming for everyone.
ERIC GRIMSON: If we could make that accessible to them and they use that to change careers or to start an enterprise or do something, how can that be anything but good?
SARAH HANSEN: I'm Sarah Hansen. My guest for this episode wears many hats at MIT. He's taught computer science for almost four decades and serves as MIT's chancellor for academic advancement. He also serves as the interim vice president for Open Learning at MIT, which OCW is a part of. So, yes, that technically makes him my boss. This very busy man's name? Eric Grimson.
You might be familiar with Eric from his very popular introduction to computer science courses on OCW. There's 6.0001, Introduction to Computer Science and Programming and Python, and 6.0002, Introduction to Computational Thinking and Data Science. He also has an intro to Python MOOC on MITx, which recently surpassed two million enrollments. For this episode, we're going to break down what makes his introductory computer programming courses so effective and what he recommends for newcomers to the field.
To start, I was curious what computer science-- and more specifically, his specialty, computer vision-- looked like when he first entered the field.
ERIC GRIMSON: I started in computer vision 47 years ago. And so it's fun to see where it's come over 47 years. In 1975, it didn't do very much. AI was something you scraped off the bottom of your shoe. And today, it's everywhere. It literally was punch cards, which you only now see in museums.
The experience was, you would go to what's called a teletype. You would type in these things. It would be a set of punch cards which have holes in them that would then get read in order to read in instructions. If you wanted to run a program, you got a budget because it cost to run on a computer. If you had an infinite loop in your code, you were in deep trouble. Because it would just keep running and burn up all of your budget, and you were done for the rest of the term.
To run it, you submitted your deck to an office. And you waited an hour, and you came back to get your printout. You can imagine, this was not fun. Students used to walk around with these boxes of punch cards in them. And the worst thing that would happen would be you trip and fall, and your cards now are spread out all over the floor. And you have no idea how to put them back into order. You don't want to program that way.
SARAH HANSEN: Clearly, we've come a long way since then. Now we have autonomous vehicles, face recognition, even technology-assisted surgery.
ERIC GRIMSON: We built some of the pioneering systems for what's often referred to as image-guided surgery. The idea is, subject sadly has a brain tumor. It needs to come out. You want the surgeon to get it out without doing any other damage. Subject will go through an MR scan. We'll build a very detailed three-dimensional model of that subject, so all of the different tissues. Here's cerebrospinal fluid. Here's skull. Here's white matter, gray matter. Here's motor cortex. Here's the tumor.
Then we very accurately align that with the actual patient on the operating table. And it lets the surgeon have X-ray vision. They can see inside the patient. They can operate through very narrow openings, but it's as if they see the entire patient opened up.
SARAH HANSEN: Helping people enhance their skills and abilities is something Eric cares deeply about. I asked him about bringing people into the field who might not ever have considered a career in computer science.
ERIC GRIMSON: One of the things I love about MIT is that I think there's a deep-held belief that anybody with enough curiosity ought to be able to explore a field. And we ought to be able to teach at a level that opens it up to them.
Now, this is a little bit misleading. You want to do quantum physics, you need some math background. But to me, when I hear young people say, "I'm not good at this," or, "I really don't think I could do that," my reaction is, you haven't given it a chance. My career at MIT, I've almost always taught large introductory courses. My colleagues tell me it's because I'm not capable of teaching advanced courses. But my view is, that's the place where you can reach out and grab somebody's interest.
SARAH HANSEN: One of the most important things about teaching an introductory course is making sure your audience can grasp the material. This is something Eric gives serious thought to. And it's part of what makes him such an effective instructor.
ERIC GRIMSON: I think there are two parts to how I would approach trying to explain something. The first one is maybe a little silly, but I think it carries with the student. And I'm doing it now. When I'm talking, you'll notice when I'm gathering my thoughts, I pause.
I do that because when I was a junior faculty member, a senior colleague was teaching a course I was helping with, he was a card-carrying member of the Actors Guild. I don't know what he had done, but he was an actor. He talked about how a verbal tic-- um, and, er-- can just annoy a listener to the point where they start tuning out. And so part of presenting is being conscious of how you're projecting, how you're saying things, how you are interacting. Because it should be a conversation.
What I always try and do when I'm thinking about presenting a concept in class, especially a complicated concept, is to try and put myself in the position of the student. I know this stuff. At least, I should. I've been teaching it for 40 years. But don't just assume that I know it.
What are the places that might be confusing? What are the detailed steps? Something may look obvious to me. It is not to a novice in there. My explanations, I hope, come across as this very specific, very logical sequence of steps.
One other trick that I've learned over, again, a long time of teaching-- and this, I think, surprises some of my current students, and I've been teaching this class for a very long time-- I'll do a complete dry run the night before at least once, twice, sometimes three times. I want to know the exact timing. I want to know where I need to hit a certain mark in my class.
But also, my experience is, if I in my mind say, "oh, I know how to explain that" and then I get up in front of 600 students, and I get in the middle of the explanation and I go, oh, crap. I just messed it up. I raise it because for people that want to be a teacher, practice. Rehearse. Go through these things, because it will be natural when you're in the middle of that explanation.
SARAH HANSEN: I'd like to talk for a minute about your use of specific examples in your lectures, particularly, I noticed you used a New England Patriots example to explain and engage.
ERIC GRIMSON: Well, I won't do it this year because they're not going to do nearly as well as they used to. But one of the things I try and do when I'm thinking about examples is I'd like to pull in something that doesn't feel dry and boring but can relate to something a student has interest in. It might be something from biology, where it's COVID-19 and how do you think about actually controlling that, which is a lecture that we do in one of our classes.
I used the Patriots just because I happen to be a fan. I've been in New England for 47 years. But I also knew that there were a lot of students in the class, whether it was the Patriots or some other team, it was something they could relate to of, how do you think about clustering players? Which was the example we did. We were using grouping to try and categorize players.
And so, are there physical characteristics that would tell you what this player is likely to be able to do? Whether you're doing a football fantasy team or not is irrelevant, but what you want that example.
SARAH HANSEN: Another thing that makes his teaching so effective is his emphasis on student participation.
ERIC GRIMSON: For many people of my generation, the phrase that's sometimes used is they're the sage on the stage. They go down into the well of a big lecture hall, and they give a performance. And some of them are phenomenal. There are great teachers at MIT and other places that really hold an audience well.
But it's a performance. It shouldn't be. It should be a dialogue. It should be a conversation. That's why I think skilled teachers of a newer generation realize it's that dialogue, it's that engagement that's as important as the performance that you're putting on. You want a partner in exploring a journey through material.
SARAH HANSEN: In keeping with Eric's emphasis on audience engagement, we asked you to send us some questions you'd like to ask him. We gathered some of our favorites from Twitter, Instagram, and YouTube.
SARAH HANSEN: What advice do you have for medical students interested in computer science and its applications to medicine?
ERIC GRIMSON: Great question. Study it. It's going to change medicine absolutely dramatically. Take some courses in computer science, especially in machine learning. It's already changing the field, whether it's discovery of new drugs or it's dealing with better diagnosis or it's dealing with just personalizing medicine. Health care is going to change dramatically over the next 5 to 10 years.
And if you're not comfortable with the idea of using computation, thinking a little bit like a computer scientist, you're not going to be the best physician or surgeon or clinician that you could be, absolutely crucial that you be comfortable with those kinds of ideas.
SARAH HANSEN: From Instagram: what is the best way to get into an AI or machine-learning career with little experience in the subject?
ERIC GRIMSON: Go online and take a course. That's an obnoxious plug, but go online and take a course. I would add two things to it, which is, don't be intimidated. There's a lot of deep math behind cutting-edge AI algorithms. And if you're really interested, go study it. Getting a sense of what those tools can do doesn't need a ton of background knowledge.
But take a class on it. Take a couple of classes on it-- the same way that in medicine, if you don't know some computation, you're not going to be successful. It's hard to find a field today where if you're not comfortable with what AI can do, you're not going to be as successful. Go take a course.
SARAH HANSEN: I think you'll appreciate this one. This was from Facebook. What is the worst computer science joke Professor Grimson has ever heard?
ERIC GRIMSON: The worst computer science joke, oh my goodness. I can tell you my worst joke if you really want to ask. The worst computer science joke... Well, three programmers walk into a bar and put up their hand with two fingers raised and say, "We'd like three beers please." Why is that a really bad joke? In computer science, you do what's called zero indexing. You start at 0, 1, 2. So for a computer scientist, two fingers means three.
SARAH HANSEN: Yeah, that's bad.
ERIC GRIMSON: It's really bad. It's really terrible, absolutely. [Eric and Sarah laugh]
SARAH HANSEN: Terrible jokes aside, Eric cares deeply about sharing the joy of teaching and learning. His enthusiasm is contagious and has translated into one of OCW's most popular and influential courses. I asked him why it's so important to him to share his work with the world beyond MIT.
ERIC GRIMSON: I'm going to give you a quote from Rafael Reif when he launched, with help of some of us, MITx 10 years ago. As Rafael said, there are tons of talented people around the world who will never have the good fortune to be able to come to MIT, because we're a small place, but who are perfectly capable of handling MIT-quality, MIT-hard material. If we could make that accessible to them and they use that to change careers or to start an enterprise or do something, how can that be anything but good?
That's really why I am a huge fan of OCW, I'm a huge fan of MOOCs on MITx, is I hope I'm a small part of helping somebody improve themselves. Sarah, if I can give you a little story, about five years ago, I got a letter in the mail, physical letter in the mail. It was from a young woman in Texas who was writing to say, "I just want to let you know, I just finished your MOOC."
She said, "my background is I have a bachelor's degree in Russian literature, and I have been unemployed for two years--" not a lot of jobs in Russian literature. "My husband got tired of me complaining and said, on a dare, why don't you go take a class? So I took your class, convinced that I would do really poorly in it, and discovered I liked the stuff. I was pretty good at the stuff.
I took four or five more MOOCs." And she said, "and I'm writing to let you know that I just started my new job as a project manager at Google." The fun part about the letter, why was it a physical letter? But it was wonderfully touching. She said, "I know it doesn't make a big difference, but please find enclosed a check for $50. It's my way of saying thank you."
SARAH HANSEN: Wow.
ERIC GRIMSON: It was a nice gesture. My point of this story, if myself or some other faculty member can have that impact on somebody to get them a little bit of a nudge-- they worked hard to make it happen-- but to provide the basis where they now improve their personal setting, why not? How is it anything but good that somebody is doing a little better because we made materials available to people?
SARAH HANSEN: If you're interested in delving into the world of computer science and programming, check out Eric's course materials on OCW. All of them are shared under a Creative Commons license, which means you can keep them, remix them, and share them with others, all for free. Thank you so much for listening. Until next time, signing off from Cambridge, Massachusetts, I'm your host, Sarah Hansen, from MIT OpenCourseWare.
MIT Chalk Radio's producers include myself, Brett Paci, and Dave Lishansky. Show notes for this episode were written by Peter Chipman. Eric Grimson's OCW course site was built by Shiba Nemat-Nasser. We're funded by MIT Open Learning and supporters like you.
And for those of you who are not done with the bad computer science jokes, here are a few more:
So why are computers not good boxers at all? Because their barks are always worse than their bytes, B-Y-T-E-S. How did the professor know how to teach computer science programming to the impatient student? He taught the student about computers bit by bit.
What did the computer do on its much-awaited vacation at the beach? It had a great time surfing the net. Thanks, everyone. I'll be here all week.