Teaching Computer Science to All

Teaching Computer Science to All

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The session today is about, computing. For all and obviously. It has entire intersections. To. The last panel and, the panel's earlier and the, way I interpreted, is, to. Mean teach computer, science very, broadly across, disciplines. Across different, stages of Education and, across. Geographies. So. Well. I guess I forgot to tell you who I am, it's. Not important, but the, mutable. CMOS I have been a professor here for 30 plus years and. Particularly. Excited, about this, important. Time at MIT. The. Last time I think MIT. Had a new school or college was I think 1951. The Sloan School so. This, doesn't happen every day so 80 years later is something, to celebrate and, reflect. So. We have a. Panel. Of very, distinguished, educators. And researchers, I. Will, focus on the education, aspect given. The day so. I will introduce every. Panelist. Separately. Our. First. Panelist. Is Professor, Anant Agarwal, who. Has. Been a professor at MIT for, even. Longer than I have, not by a lot and, he's, the, CEO of EDX. In. Learning about him he's, a remarkable. Something. I discovered is, an anon thought the very first EDX. Course on circuits, and electronics from, IT which. Drew a hundred fifty five thousand, students. From a hundred and sixty two countries. I think, I would say he's well qualified, to talk about, geographies. And so forth. How. Many computer scientists does it take to change a lightbulb. Okay. So. Uh, thank. You. Really delighted to a chat, with you today and a, brainstorm, about how, we can increase access to, computer. Science but, what is the problem here to, give you a quick, idea of the problem you're trying to solve. There are, 1.4. Million, CS. Related, jobs available, by 2020, and we. Are producing a pitiful, 400,000. Okay so we are off by, a, mere. Factor, of four. At. The same time, we. Don't have place in our classrooms, to hold students. The. New York Times article that, you see a picture of here talks, about how, in all the classes in computer science, people. Could not get, into those classes and was talking to my. Dear friend Regina.

Ballet And she was telling me that in her machine. Learning computer science class at MIT there, were so many students, in the classroom is over four that. The police will call in and they, had to then there to take the students out because the refuses refused to leave her classroom ok. This, this. Is what is happening this is not a third world country where people are fighting for scraps of rice these. Are people these are people fighting for bits. Of knowledge in, computer science. And. Here's the challenge on campus our campuses simply cannot teach the number of people you want to teach and. These numbers are true everywhere. University. Of Texas at Austin just, launched a online. Master's. Degree on, EDX for $10,000, and they, gave us these numbers, 1,300. Students apply for their masters in computer science on campus they make 100. Offers. And, 30. People come to campus. Three. Percent I mean. This is insane. When. Everybody, around the world can go in and type, or search you know I, don't, need to have a library in my house I can go and type search digital. Technology, has solved, so many problems, for us where we, all have ample. Access but. We've not been able to solve one of the fundamental, accesses, of education, and and you, know not many people would argue that education is human right but. Then we have this keeper somehow physical, space in classrooms, that do not allow us to teach as many people as we want to teach so. One solution is. Digital. Education, particularly, modular, digital education and let me talk a little bit about it a digital. Computer science learning can't scale so. On edx.org, as. An example edx was a body. Is a non-profit, founded, by Harvard and MIT where, about. A hundred forty institutions, many, of them represented here like you. Know Georgia, Tech and and and others offer courses to people from Cornell. And. Others from people all over the world and, we. Have eight. Hundred plus computer science courses and eight. Million, unique learners, from all over the world taking, these computer science courses and in. Case you're wondering you, know are they really completing them yes two hundred a quarter, of a million students, just, in the space of about six. Years have earned quarter, of a million certificates. In computer, science courses. So. It is possible to teach computer, science at scale we can, teach it the high school level we, have a number of high school courses on EDX. A.

Number. Of them high school AP courses. Harvard. Has a course on AP, computer science principles Berkeley. Has a course on beauty. And joy of computing and. Trinity on veins in her label sin here, so. Hal Abelson, in. MIT and end up a part time at Google and some amazing work in creating. The App Inventor awaited. A way to build, teach. Computer science and build computers build. Applications, for mobile Trinity. Trinity College has an amazing course on EDX and Purdue as, well and, so we have 1.5. Million. Unique, high school learners enrolled are, taking, these high school level courses in computer science on our platform, MIT. Is, doing an amazing job have. 90 plus courses, on EDX, with. 1.7. Million learners. On. Our platform and here I'm broadly consuming it as you, know a data science computer science and. Related. Courses with, that 225, thousand certificates, earned and Eric. Grimson who's sitting here probably, single-handedly, contributed, to a large, fraction of them an, etic and John Guttag teach, the. Mitx the MIT introduction, to computer science end up. Python. On, EDX. And what. About the stress here is not not only is it the free course and people, are earning certificates. But, this. Is accessible, in the ADF sense you. See this learner here at Varga he is from IIT Madras in India and. Someone, want to guess what's unique about him he completed, this MITx. Crimson's. Computer, science course on EDX and. This. Is the same as, six. Triple o at. MIT. And he. Completed this course anyone. Guess what's special about him. He's. Blind so. The, platform is weak AG, 2.0. Double-a compliant. The. World wide web consortium that has the weak Eric to standard they themselves have courses on EDX at the Houston csail front-end. Web developer, and here's another student, Larissa who's completed their program on EDX. Online. Courses can also help meet campus demand I mean, isn't, it insane that you're not using digital technology. To solve the problem that. Involves. Teaching digital technology, it's a bit you. Know better, circular, you, all remember meta-circular evaluation. And scheme and stuff and so we should be using the, technology, we create to solve our problems of the same technologies, so, Georgia Tech, a. Couple, of my Georgia Tech colleagues or friends are here. So Georgia, Tech doing their enrollments, in the introduction to computer science course. At Georgia Tech was, overflowing. So. What they did was they. Allow their students to, take their fully online course on EDX one other person online or they can take the campus course and our. Friend as we Galil was. A dean there tells me that, 82%, of them rate the online course as better than the campus course and today. 60%, of Georgia Tech students are self selecting into the fully online course. Mit. Has done the same thing although. MIT did it with a circuits course so. I might hear the circuits course where a half the students took it online 100%. Online not blended, 100%. Online and half, took it on campus and, this. Was an experiment, and they. Even gave the students the same exam and, the. Research papers written by an, marshal on the, study that, talked about how the results, for the exams are pretty similar, so. Online courses have come of age the. Universities, like Georgia, Tech and MIT are giving campus students credit for, completely online courses. In. Addition to access so far I've talked about access and how we can use these courses to solve. Some. A major access, problem how do more people learn computer science at the high school level at the college level and, also. You. Know how do we. Solve. The problem that we face in colleges that our classrooms are simply not big enough regular, just told me that she.

Had To cut down the enrollments, in the class to 90 because MIT did not have a classroom big enough to hold the number of people she wanted to hold this, is insane. Folks I mean this is nuts, help, me can you imagine real estate I guess Cambridge real estate is a different thing so that's a real constraint I know, the rents we are paying at EDX, the. Other important, thing is that there's. Another major challenge in the world which is this upskilling, challenge, where various. Studies have shown that in, within the next ten years half. Of today's jobs will have to change in one way or the other people will have to learn radical, new skills or. Lose, their job because, automation. And AI you, know all, the things that Regina and company are doing it's all your fault and so. Uh so, uh so, the. Whole planet, has to upskill we all have to upskill, and how do we how do we get these skills out to people how do we train people how do they learn many, of them are working in companies many of them looking for jobs no. Way they're going to come to a campus to get a master's degree or a second bachelor's no way no way on earth nor. Do they have the time to, learn online and, do full one-year master's or, multi-year programs, we, need modular, credentials. We. Need modular, approaches, to teach. People and and the first picture I showed you with those Lego blocks it has the answer which is we need modular, education, and at. EDX, the. Number. Of modular programs MIT pioneered, the new modular program called micro masters sea masters micro. Masters no computers, micro. Computer so the micro masters are one year two year-long micro. Masters are about 25% of a master's. Degree and fully online and people can take these and complete them and get. A, campus. Credit if they get admission into the University so, you can, get a micro master's in MIT from, MIT for example in data science for about $1000, today you, can also do radical crazy, things with, marginal. Programs, you can stack, to. My knowledge is the world's first stacked, multi-institutional. Degree so. Mit has, a micro, master's program, in supply chain management on EDX so. Arizona, State MIT, the number two ranked program in supply chain Arizona, State is at number three ranked yesterday why, do we need to create a full master's degree, let's, take mi t--'s micro masters let's, just create the complementary, part MIT. Has four courses they, build the six courses and the launched a master's in supply, chain management on EDX modular. So, education, would become like Legos it, will go online, campuses. Will have online learning and campus, physical, learning at the same time and and, you know I see a world in the future where, this kind of modular, digital learning can, really address the kind of needs that our planet faces in computer science and other frankly. Other, technologies. Thank you. Our. Second panelist is Professor, Regina Basel live from the compar computer. Science department, here in. Addition to being a recent, winner, of the MacArthur award for. Her. Work of developing machine learning methods that, enable computers, to process and analyze vast, amounts of human, language data she's. A recent, recipient. Of the James on teaching award one of the major prizes. Of the institute for teaching. Thank you very much I learned that there are actually many other recipients, here on the panel okay, let, me start. So. What. Am I supposed to be doing Oh. To, do well. Yeah. Okay. So. I arrived. To MIT in 2003. In. When he arrived to MIT in 2003. Ai was not a popular term and we. Didn't have like hundreds, of students who wanted to get into the classes and at. A time machine, learning, classes, were taught all on graduate, level so there was no question you. Know teaching non major machine learning we barely had you know majors who we're studying. It and measures which were graduate students so clearly. You know the situation, change and if you don't need to go far you can just open a newspaper and, you would see that you know a, AI, and machine learning there's, all different types, of miracles, across all different disciplines, and. You. Know our students, read newspapers, and of course their interests, in machine learning greatly, increased so. Around. Maybe six years ago to me yaqula lahu is a professor here and myself we said we actually have to, start teaching this class in the end the graduate level and that's how six three six one of the very popular.

Classes. In machine learning was born and, you can see for the few years when. I was teaching it that the enrollment steadily. Increased, in this class and. Originally. We thought oh just once, a. Year now, we're teaching it twice a year so but what I want to tell you that there is something else that happened what. We noticed. Said as we continued teaching the class the composition. Of the class greatly, changed originally, this class was designed for. Non major computer, scientist, and you can see in 2013. Eighty-three, percent of the students, weigh in computer, science if, we are looking at the chart, in, 2017. You can see, almost. Half of the students in the students, in the class actually non-majors. And they, cover almost all, the, different. Majors across MIT, they're. Not computer, scientists, and this was a great new scribe because we really can see noir with one class we can deliver the goods for. The whole community, however. The. Part that you cannot really see on this chart is what, happens, to non major and was when they had take this class first. Of all they have much higher rate, of enchants, of dropping from the class and second. Their grades are much lower than our major. Than. Our majors, so. The, question, is if you still want the students, to take these classes and to benefit, what. Do you want to do so, one answer which is really unsatisfactory. Answer, is to say you know what we're gonna do a remedial, class we're gonna take a normal machine learning, class water. It down and make, it fun on major so that they can succeed and, you can say now the landscape, of research totally changed now we have all these big building, blocks we have all these different machine, learning packages. Which. Are very high level so maybe we. Can just teach them how to use these. Packages. And that's it. So. I think it's wrong approach, what, we really need to do is, to, enable. People, who are users of machine learning technology future uses, of machine learning technology really, to think about modeling. What. Are the, problem, formulation strategies. What kind of tools you can solve, you. Can use to solve it now let's just look at the curriculum of standard. Machine learning class that we are teaching that, everybody are teaching it's you know there are variation, of this class so what you would see here they cross like lectures that they put on my slide the. Vast majority of it is specification, so, for those of you who are non majors and, intake machine learning class it is one technology which is really powerful technologies, just one building low block and we, are looking at different ways to build this block inside we're not talking about what beautiful things that you can build from these things how. Do you need to select the right type of blocks which is focusing, on, technology. And you know to me one of the biggest surprises working. With MIT and the graduate who are majors, who did very well in the class but even they don't understand, how to put, these blocks together how to decide, which, of this technology can be useful, and how to move forward so, the, topics, that are really, absent. Which. Really crucial, for using machine learning technology across, disciplines. Are you, know kind, of core, pieces of technology, like making. The models interpretable, if your models make the prediction, and you're using it in healthcare, you're using in financial, industry, how, can you explain what is it doing and it's particularly a problem when we're thinking about deep learning models, we don't teach in another big. Question, which is a very useful question, what do you do when you are training your model on one type of data and you need to apply it to another type of data very, very common, scenario across.

Disciplines. We, don't talk about it, and. The other one is a sparse data for the vast majority of applications, we. Don't have huge, data sets what are we what tools do we give to students, to, address these questions and of, course there, are all. The different kind of scientific paradigms, that people are thinking about and talk about science, like causality, and others they are not addressed in our classes, and even. When we're thinking about evaluation when, we want to make sure that the student, and the user understands. How you actually. Are using technology, is doing, the right thing we. Don't have any. You. Know any, material. And there are lots and lots of kind of emissions. That, are in our standard, curriculum so. What we've done I stopped, teaching a six or a six and, we started teaching a new class that just came from teaching the class with 90 people. That. We have in the classroom, it's, called modeling with machine learning from, algorithms. To applications. And. The. Idea is really to defocus, from classification. We do teach you know few classification. Algorithms, the students understand what are they doing but, really, to focus on the idea how, do you build from it what do you need to be understanding. Thinking when you are applying, and, and, creating, new formulations. And the topics that I just show you on the previous slides, are really, kind. Of developed. In this class. Another. Point. That is important, is the teaching style what we realize that when you're talking about non-majors. You're looking at the huge diverse, audience, you people you have people who are math major physics, majors, who are much. More advanced than others, in terms of linear algebra, and probability, you have people from other discipline, I wouldn't, name them but which, maybe need more help, and. They. Approach. It. From, that other college, you know that was created, before computer, science college. The. The. Point that I was trying to make we realize that you know teaching the lecture teaching the material. The core techniques, in the class is a bad idea, because. For. Some it's really easy for some it's really hard so, we kind of recorded. Technical, lectures, and the students, can go using MIT our students can you know go listen to lectures they have exercises. Which, they consult and then we are using the classroom, time really. To make the discussion, and to think about different application. Scenarios, and. The. Biggest surprise to me that actually the closet we are teaching I we advertise it for non-majors. 80%. Of students in this class are majors, of, course six majors, but you know what was a surprise, to me that this, majors, many of them took six oh three six they know kind of basic algorithm, I was. Surprised to the extent that they cannot understand, how to apply, them and why. Do you select technique, a versus technique B so, I think that it's. Useful both for majors, and non-majors and. Through these discussions we actually kind of learning how to move forward and finally. We are really focusing, on connecting, to other disciplines, like chemistry. Biology. Linguistics. And what we are expecting, moving forward, that we are going to create specific. Sections. For, the sub discipline, so that the faculty. Part, of our new College can help, them. You, to do. Modeling which is specific, to their area of study thank you. Third. Panelist, is Professor. Marie, desert, dance C's, the inaugural Dean of the call of the. Colors of organizational, computational, information, science at, Simmons, University, C's. Has. Done extensive research in. Artificial intelligence, and computer science, education as, well this, is well known for their leadership in broadening, participation, in. Computing and, also having talked to her she's, particularly passionate about k-12, education. And I think she would be talking to us about this matter now. Yeah. So I'm, sorry I wasn't here this morning to here don't Tony to rose to say that he was the only one who was they don't even know who that is. The only when talking about k-12, computer science education but me too I, think it's really important and I think it's essential actually.

And. I'm gonna talk about why I think that so, I'm, not going to talk so much about the content of computer. Science or what we should teach to k-12. Students, although I think that's really really important, to be thinking about but. I want to I want to talk about how we. Could get to this place where k-12, students, are actually. Being. Exposed to computer. Science throughout, their education. And to. Do this as I, think was mentioned earlier, today is very, challenging in the United States because we have a very distributed, educational, system and what that means is that every single state, has to. Develop its own solution, for, computer, science in the curriculum and in, some states every single school district has to do that so. It's really really a challenge. And it's really about leading transformational. Change and how. You get people to work together to. Really change a system that's kind of entrenched in a current way of thinking and why, do I think this is so important I think this is so important, because if, we want to change the face of computing, if we, actually want. To have. Gender. Representation. Racial. Representation. Socioeconomic. Representation. That reflects, our, society. We. Have to, get, different kinds of people into the field and the. Best way to do that is to expose. Those. People, who are not currently coming into computing, to computer, science early in a way that lets them think of themselves as computer scientists because. They're not seeing the role models out there because. They don't exist so we have to solve this chicken and egg problem and. I've become, really. Convinced, that we, have to do this by starting early. As. Early as elementary school. And changing. The way that young people think about what, does a computer scientist look like and what, do they do. So. I just want to talk about what we did in the state of Maryland, to address this problem. And, it's kind of looking, back on it it was a five step procedure, that makes it sound like we knew what we were doing but we really didn't know what we were doing until we got to the end and we said wow that worked so, I want to talk about what worked and how we fumbled, our way to something. That I think was really successful, that. Can, be. Leveraged, to, develop, similar solutions. In other states so, I kind of have this five step thing identify, the problem, gather momentum garner. Resources, solidify. Infrastructure, and build for the future and so I'm going to talk about each of those a little bit with a few lessons learned along, the way so. First identify the problem, it's. Easy to say oh we need more students. And k-12 computer science education and that's that's a very abstract, goal, but. To actually understand, how to do that you have to gather. More data about what, the current situation is. In. Order to address it like what are the nuances, of what's. Happening, in your local region in, in, the schools who. Are your teachers who. Are your students, what's, the curriculum, what's, what's, this state so, how did this work in Maryland, well in summer of 2001. 2011. I'm sorry, 2011. I, got some funding from Google, through, a program called cs4, HS to, run a workshop a summer workshop for high school teachers and we were doing this because we. Wanted to get more women into our undergraduate, degree program. And we we, thought well where would we go to get more women high. Schools that's where that's, where the students are so let's go to high schools well, who should we go to in high schools how about computer science teachers who are the computer science teachers. We. Don't know we. Don't know it turns out part of the reason we don't know is because computer, science in most schools at least in Maryland in most states is not its own Department, who's. Teaching computer, science math, teachers, maybe science teachers maybe a gym teacher here in their social studies you know whoever we can find and especially in 2011. That was the case so. We brought about, a dozen teachers together at this summer workshop, and they were so excited to meet each other that, we wanted to keep that momentum going and that was kind of the big beginning, of this whole you, know 7 year long process, and, we started, to. Try to keep it going to, create some infrastructure, we, decided, to start a local chapter of the Maryland computer science teachers association which is the national, professional association.

For Computer science k12 teachers and we're, like how do we do that I don't know let's pull up the website and let's oh we have to do an application we'll, make an application so we just did it we didn't know what we were doing we just thought that might be a good way to get started and, then a group of us kind of got together we're, doing some activities, over the course of that year and. Decided. To try to get some money to do more we. Ended up with a planning, grant from NSF computing. For the 21st, century program and, did, a landscape, survey, so, that got, us to the place where we understood, what we were facing and we could start to think about solutions so, that's the first lesson. Jumping. Ahead a little more quickly because I see my time. We. We we, got used some of that money to start bringing people together so we had a couple of statewide summits. And we, got people talking about the challenges, and the problems and, the gaps and. The. Thing that I realized was we, don't know what we're trying to do I mean we know it's like writing a PhD dissertation, we know we're trying to write a PhD dissertation, but what are the steps along the way to that you have to break it down into pieces and especially when you're doing something collaborative. You have to find a starting point that you can get a lot of momentum behind and, a, lot of people wanted to say let's, require computer science for everybody in high school and. That was a really daunting. Challenge. We didn't think we would get there very soon so we started talking about what could what could we do that, everybody in this room 120. People at the summit can agree is possible. And important. And the. Goal that we came up with was every. Maryland public high school should offer a high-quality, rigorous. College preparatory, computer, science class everybody. Agreed that that was a step along the way to the big thing that we all wanted to do and so we spent the next five years focusing. On how do we do that so you have to have a shared goal to, bring people together and, you can't just take your goal and make it everybody else's goal because that's not how people. Work so, resources, now we've got this goal what do we do you, get money so, we wrote another, grant to NSF under their cs10k, program, Jan. CuNi program that was mentioned earlier to develop an AP computer science principles, curriculum. And trained teachers to teach it so. We now have a curriculum called CS, matters which, is one of the college. Board endorsed. Curricula. For computer science principles now, there's lots out there and we. Led a collaborative, curriculum, development process, so teachers, were actually working, together to write the curriculum which i think was a really good way to do it and we, started training teachers and, doing. That work together created. A really strong team and that's, what kind of led us launch into the next phase along. The way, we, also started, thinking about who were our partners and we, developed. Some really close. Contacts. At the Maryland State Department of Education I, will say we also have people who are not. As supportive but. We found the people there who were supportive. One, of whom eventually, became interim, state, superintendent and. Essentially. Signed an executive order, saying computer. Science can count, for. This state technology. Education requirement. Which. The. The hard part to believe is that previously, computer. Science didn't count for, the computer science technology. Education requirement. So there was a tech at graduation, requirement, that didn't have any computer science in it so. That was a big. Barrier because, it's like well we've already got. We don't need more technology, what we do we need different technology, and, we we, we. Found it it, was not going to work to go through the legislation, which is how that requirement. Had been put into place but, we could do this end run to, just add another option, for students well the students really, wanted to take computer science because by this time computer. Science was starting to explode an interest, and so a lot of factors came together to. Make this all work but. You, know we had this grassroots effort, but, the reason, that things really came together and took off in Maryland is because we also laid down roots you, know we didn't just kind of get people together and talk but we found the key thought, leaders and the people who controlled, resources, who, we could get on our side and start to think about bigger change so. The last step and, this is really exciting because I left UMBC, last, year to move to Boston to. Become this new Dean at Simmons University.

Which Is a great opportunity but. I was really worried that when I walked away everything, was going to fall apart with CS education, in Maryland because we didn't have any infrastructure, we, just had some people who were working together and, I was kind of at the hub of all of it and I thought well if you pull out the hub of a wheel it, doesn't keep rolling, very well so. I spent, the last couple of years really thinking, about building infrastructure, and we established the Maryland Center for computing education which originally, was a cubicle, and a sign on the wall like, it had zero resources, but, USM agreed we could have a thing and they wrote a memo. Saying there's a thing and then, we went to the state legislature, and we said well you should really give a give, people lots of money for computer science education and, trained teachers and all of that and and we think you should give it to this Center because. This Center is. That's. Its mission and and so it all kind of was like smoke. And mirrors that coalesced, into, five. Million dollars in state funding in this year's this. Fiscal year's budget for, teacher. Preparation and advocacy, through, the Maryland Center for computing education so. That's, how things happen, and. The people who were involved. In it are now the leaders of that so. The one last thing I want to just just put a plug in is if anybody is in Massachusetts. And is interested, in getting involved with Anissa, and cs4. Massachusetts. Activity. Please, reach out to me I might be happy to put you in touch with that group and I think, Massachusetts. Should be at the forefront of this and they're not so. Maybe the MIT, Schwartzman. College of Computing could also help, with that so thank you so. Our, fourth panelist. Is Professor Eric Grimson which is my. Piece Chancellor, of academic achievement, and, also professor of medical. Engineering, at MIT you. Heard about. Eric's. And, John, gootecks class, from. How. Successful he was. Egg. Has taught more than 10,000 mighty undergraduates, and has served on, the theses as a thesis supervisor for. About 50. MIT, PhDs. He, is also the recipient of the Bose Award, for Excellence in teaching in, the School of Engineering which, I understand is the highest award in for. Teaching at the School of Engineering Eric. So. I'm going to describe. Experiences. Lessons learned from teaching, my teas introductory, CS course it's a class created, by John Guttag I gave, him a little help John. Anabelle, and I continue. To teach it I'm, here because John's actually, across campus, in lecture, right now doing, the right thing teaching undergraduates and I'm talking to you, to. Set the context it's a subject that's taken, typically, by about 900, students a year an, undergraduate class at MIT is about 1,100 students so almost all students take it it's, a class intended. For students who know very little, or have very little or no prior experience in, computing. And, interesting, to a point that I think Jeannette raised earlier, that number is dropping, because, we're seeing more students coming and prepared and those students who come and prepare take an advanced standing exam, and get credit and simply move on. The. Class started out as. A one term class we recently split it into two halves the. First half focuses. On computational. Thinking and, the second half talks, of data analysis, and computational. Experiments and I'll say a little bit about that in a second, we. Also provide, two online versions we, have put up two postings, of the. Course on OpenCourseWare, one. In as, it says there in 2008, one in 2016. The. First lecture, has been viewed. 4.3. Million times which. Is a frightening thought that that many people have heard my bad jokes and we. As you know we, taught the second MIT, MOOC and not did the first one we. Have a course that came up in 2012. On EDX, it's been offered 17, times and has, had 1.2. Million registrants. Around, the world also. A frightening thought, so. Goals. Of the course, as. I said it's intended for students with a little or no prior experience in computation. We in fact actively. Discourage. Students, who, have experience, from taking the class we don't want them to intimidate, people in, the class and. I'm going to borrow from two great colleagues before me one. Of the goals is really while the students do learn a programming language in this case Python, the, goal is to focus on computational.

Thinking Thank You Jeanette for creating that term at least I credit you with creating that term computational. Thinking computational. Methods not the specifics, of programming, this is not a programming, class it's, how to problem-solve, how to think a little bit like a computer scientists and that's what we want to do is change the students way of thinking and, then I'm going to borrow a comment, from Maria Chloe because. In addition to focusing on algorithmic. Approaches, to problems, we, want to show students, examples, in other disciplines so, in our problem sets in our lecture examples we heavily borrow, from. Biology. Physics urban, planning, economics whatever. We can let them see things in context, we think that really helps them think about, what they want to do, so. The primary objectives, to 30,000, foot view are, very simple we. Want students to learn approaches, for, decomposing, problems into logical, steps we. Then want them to learn standard, approaches, for converting, those decompositions. Into, algorithms and finally. We, want them then to convert those algorithmic, descriptions, into actual program, especially. Understanding how to make efficient implementations. But notice we start with the. High-level view of this how do we get them to think computationally. You. Can read this I'm not going to go through it we use basically the things you would expect the standard, tools of any good introductory, computer science, class but. I'll highlight that in addition, to abstraction, and modularity which. Are in every good intro class we. Really talk a little bit more about recursive, thinking and how, you can use that to design algorithmic. Solutions, in a wide range of areas we want students, whenever they see, a new problem to say how can I break this down into, a simpler version of the same problem how do I approach it algorithmically. I, want. To talk briefly about the campus version and then the online version, on campus. We. Mix online, methods with, traditional methods during, lecture we'll take stops and we'll do what we call finger exercises, a short, little question that the students do online we look at the responses, we. Also assign, those finger exercises, during the week as well as weekly problem, sets and a big factor for us is to have those, problem sets initially. Graded, automatically. By an online tutor our. Experience, is that instant, feedback is, really valuable, I know. We got lots of computer scientists here looking for that missing close paren, is totally, annoying and the fact that your code doesn't run is irrelevant instant. Feedback helps, students very quickly identify, when they don't know something and go back and look at the text so we use that a lot but. In addition to that we also require, students, to come to. An office hour with an undergraduate or graduate TA, and explain. What they did so we have to get a check off where they have to talk about why. Did they make those decisions where do those where do those solutions come from a little, bit to catch the people that are getting too much help from others and a little bit to actually get them to explain it, one. Of the things I want to do I want to take very briefly because I still got a few minutes here about the young woman in the middle because in. Addition to them hearing John or I tell bad jokes they, go to tutorials, and that's. Taught by graduate students it's a great thing to do but the young woman in that middles image is I think a great story, she. Took this class many years ago as a fresh one, convinced. That she hated computer, science because, her father was an MIT alum and he was a senior person at IBM, absolutely. Convinced she was not going to be a computer scientist took, the class discovered. She loved computer science finished. A major in computer science came became one of our best TAS. We actually have recorded, her on video which what you see here going, through tutorials, and. Today, she's. The chief of staff to Drew Houston at Dropbox so. You know you can discover the computer science is a cool thing to do, in. Addition to on campus we do have an online version and we offer it through but. I said OCW which is really a static. Snapshot of, the course and more importantly, a dynamic. Version on thank you or not the great platform, EDX. We. Break the lectures into eight-minute chunks we, separate, them with what we call finger exercises, very quick question that gives you a sense of did, I understand, what was in that trunk if not I go back and look at it again, the. One difference we use here is we. Do not have no matter how many times I've begged Rafael the, budget to staff this and so, we use what we call community TAS, it's, an interesting experience which are not I'm guessing other people on EDX do these, are people who've taken the course in the past they volunteer.

To Serve, as online TAS, and they do it purely for the glory no, money and they, will do it multiple times we've had on like sorry job community. TAS who have done it eight or ten different times and it really helps the students get a sense of how to ask their questions, I want. To give, you one, quote. From a student who took this class, sent. Me a note a couple of the weeks ago she. Said quote your course has really changed my life I have a degree in civil engineering but, was having trouble finding work in that field where, I am which happened to be the state of Utah and I, ended up as a program, manager for software, developers, for a few years I decided. I wanted to pick up development, in your courses where I ended up from. A recommendation I found online I finished, it in April and with no further education, was hired into a back-end Python. Development, internship, in May and just, converted, that internship, into a full-time position as of Monday it, was largely thanks to the knowledge I gained in your course a real life-changer, now, I'm sure I'm going to get nasty messages, than people who didn't like my class but. It is nice to hear, that but he can take one class and discover that they've got a way to go. So. The take-home message. We. Want to expose students without prior experience, to computational, thinking some. Will go on to be CS majors we're leveling, the playing field and, that's important, but. Many of them will use that computational, thinking in other domains and thus, we want students to learn how to think computationally, design systems, that, leverage modularity, and abstraction use. Them to complement, theoretical, explorations, and physical, experiments, with computational. Analysis, and exploration, but. We also believe that exposure. To computational. Thinking provides, a different mode of communication, you. Talk differently, when you're thinking algorithmically, and as. President Rifa said we think every student here should be bilingual speak. Computation. And something, else in this, course for many students is a first step in that direction Thanks. Fifth. Panelist. Is dr.. Jim. Kouros who, is currently the assistant director, in, the computer, information science, and engineering at, the National Science Foundation on leave, from. The University, of Massachusetts at Amherst he. Himself also has multiple awards, in teaching.

In. Fact. It. Was difficult to find what to say so. He's. A nine time recipient, of the odds-on Teacher Award from. The. National. Technical University and. This appeal of the outstanding teacher award from, the College of Natural Science and Mathematics at. The. University of Massachusetts among, many others thank, you. So. Thanks, very much um I, noticed, you counted that introduction, against my time I guess that's okay. It's. Always oh. Yeah it's. Always tough being the last Speaker of the day but I'm so pleased to be here and I wanted to start by congratulating you all and those congratulations. Come not just for me but everybody in the size Directorate, at the National Science Foundation, and when I was running out last, night to catch the plane France córdova, our director, knew I was coming she said make, sure you say congratulations. From me too so congratulations. From all of us I mean what you're launching here is really, historic, and actually I want to come back to that at. The end so, one, of the things about being the, last speakers a lot of people have said, things. That you, wanted to say and in fact is Rob here Rob, had my slide I saw one of his slides I'm like I've got that slide Rob. But. What, I want to talk about are really. Three things and then I want to end up with some some high-level just, just comments, here this is probably the only place I can go and say there's an interesting right hand rule here but I want to talk about computer science for all what, we call cue, computing, and undergraduate education, and broadening, participation in, computing and I'm going to focus a little bit more on the programmatics, from the NSF side but, Jeanette's already done some of the background for that so I actually I, can. Go through that pretty quickly pretty, quickly, oh. Sorry. Seems, like everybody's, having trouble with the clicker. Man. Seems. Like everybody's, better than me -, can. We try again okay, all. Right I'll just go on with my talk I'll just talk to the slides okay well this is actually not how the right. Hand rule works here but I'll, start with broadening participation in. Computing we've talked about that some about equity and access. For, all the B PC alliances, were actually launched at the National Science Foundation, in 2007. People have mentioned Jan CuNi name multiple, times it turns out that's when she's can't when she came, Peter. Freeman Jeanette, Farnum Shaheen Ian who was the ad between, assistant. Director between Jeanette and myself and myself we've all supported, this tremendously, I will only point out that also in 2017. We're, launching a pilot where we're asking, we want this to be part of the entire community's, responsibility, broadening, participation in computing we, have a Dear Colleague letter, and a pilot, where we're requiring our PI's to do something.

Meaningful, Right, and there's. A lot of background there but, we want them it's really part of the whole community it's something that's been part of the strategic plan, for sighs, for now for quite a long time. Okay. So I really wanted to start with computer science for all and I want to go on record as being the. Worth person, now to, talk about. Computer. Science education and, education broadly at the at the K through 12 level so as you've heard before the idea is to enable all students is about equity and, equity. And access all students, to have access to a high quality. Educational. Experience in, computer science in K through 12, developing. The knowledge base developing, the capacity as. Murray said for, teaching that rigorously, that also includes. Teacher. Professional. Development, NSF. Committed, in 2016. Where's, Randy so working with OSTP, and the Department of Education. And nonprofits, putting in 120, million dollars over five years to actually build. This and and so I feel, like this, is gonna be this is a homerun it's a homerun already I feel, coming in I joined NSF in 2015, so I was born on third base as, far as this is concerned right, that. Again starting, in 2010, I think Marie mentioned cs10k. Right, and so that was a project that. That actually Jayne Cooney and others started in 2010. To bring ten computer, science to ten thousand students by 2016. Ten thousand teachers right we, didn't quite make it but we actually came pretty close and and you, know cs4, all sort of grew out of that and and as has been mentioned before one. Of the things two things actually. In. Computers, in. Cs4. All computer science principles and, also exploring computer science, CSP. Is the new it's, the second, AP exam it does not replace. The. Programming, AP. Exam. You see the big ideas their programming is part of it but just a small part of it it's all the computational, thinking that, we've been talking about before it's about creativity, it's about the use and application of. Computing. And computational, thinking and. Data and, algorithms, instantiated. Through programs okay. So. You know the challenge we faced was how do we scale this and you. Know Jeannette gave an example of school, districts I live in Massachusetts in, North Hampton we, have four hundred four school districts in North in in Massachusetts. Right I spent. Two years when, I was an assistant professor working with the North Hampton school system to, try to get computer science and you know helping a math teacher there as it turns out getting it in you. Can't do that right there are just too many school districts everywhere so how do you scale. Really. Good ideas to make a national move. The needle nationally, and this was done through. The introduction, of this new computer science. Principles exam. So to me that was just like that's the light bulb that went off in in Jan's or somebody's, head, you know circa. 2011-12. Okay so, I just want to show you some data everybody seems to love data so this is data from the AP, Computer Science exam and I want to talk here about diversity. Right, so what you see on the in the three graphs as, a function, of time the, number of female students who are taking an AP Computer Science exam from. What does that start. 2007. To, 2018. The number of black and african-american students, in the top right hand corner and in the bottom right, hand corner the number of Hispanic, and Latino students who are taking that so to. Me this, is a real this is a real home, run and a really good thing for the community and, people have been working on this for ten years and I think we've. Got a lot to be proud of it and it's going on the little table over there just, in terms of the raw numbers going up you see in the graphs but seeing the percentages, changing, in the number of women and underrepresented minorities. Taking the CS an, AP, exam they're also, ok. Sojanet. Actually was kind she put up a whole bunch of size. Solicitations. So I'm only going to put one up here the one you miss Jeanette because it only came out two weeks ago okay, and. That's okay and. This is all, I want to say this, is about well, it's not just about, let. Me show you there's two quotes from the solicitation, here this is about rethinking the role in the positioning, of computer science education, there's something about x plus CS we don't put CS first anymore, I'm just telling, you that when we talk about that. But. Really thinking more broadly about, a holistic restructuring. Of interdisciplinary. Degree pathways, right and so I. Think proposals. Are due June 9th so if you're from an institution, that's thinking about things. Like computing, and undergraduate education, I want.

To Say this was built for you with, exactly, the kind of things in mind that were thing about here at, this workshop okay so I'm gonna finish up this is my last slide this is the slide you saw Rob put. Up although he had Illinois data there and I have Toby's, survey data there for the number of computer. Science computer engineering, and informatics students, who are taking classes are newly enrolled majors, as a function of time so. Somebody. I think, mentioned. The the, Snowbird, meeting this was a, meme. Picture, the tsunami, of students that were about to come in in, 2014. And actually of course it's come to, happen so so. It's not news that we see this increase. In students I guess the, other thing and Rob didn't have this on his slide so I want to talk about this some, we're. Seeing multiple. Tsunamis, and actually this gets to Greg Morissette's, question, right so yeah we're seeing all these students come in but we're also seeing students come in now, I think because of some of the AP exams that we've been doing and we're seeing students come in and knowing and having broader, interests in the application, of computing. And so the question is how are we going to respond. To that and I think that's going to be our challenge and when we think about the diversity of students we talked about gender, we talked about. Interests. We should also think about age we should think about background, we should think about preparation. If, maybe. Since I get to have the very last say here I'll go back to farnum's, talk at the very beginning, nothing. Is going, to be more important, over the next 30, or 40 10. 20 30 40, years than, education, in a technologically. Disruptive, time. That's what Farnum was talking about right so it's our responsibility as, a community to take, the lead there now you're. Starting, a new college, here you've got an opportunity, here right who, are your students, who are you designing curriculum, from, what's the model is it, students. Are 18 to 22 are going to be on campus you got to do that right but, what about lifelong, learning for students what about students from diverse backgrounds what about students with diverse. Interests, what is this College, going to do I'll just throw that out as a question, what. Is this College going to do about, this, because. There's, a very small handful, of colleges in this country, or, in this world that people look to for, intellectual, leadership in education right. And and, people have mentioned the thread models so I'll give a shout out I don't see Charles here anymore but I'll give a shout-out to Georgia, Tech for the thread models I think that really moved the needle in computer. Science right and we've got the opportunity got the need to. Do that now so, I want to say congratulations, to. All of you right it's like when you I had a colleague when I got a DARPA but we got a big DARPA Grand they said ok it was like the best thing when you launch things it's the best and then it's all the hard work ahead you, got a lot of hard work ahead and, a. Lot, of challenges to face but just a tremendous amount of opportunities, so maybe, I'll close off simply by again saying congratulations to, all of you it's just phenomenal, what you're doing here and I think we're all going to be watching very carefully, thanks.

About. 15 minutes for questions I would, like to open it up. About. 5 minutes because it, turns out that I'm giving the opening keynote at succeed tomorrow because. The opening keynote speaker has the flu so, I have to get to the airport I just, at. The risk of being presumptuous, that there are any questions particularly, for me I'd. Love to hear those. That's. My brother. Picture. They. Shouldn't necessary, features. To use computer, science, and enjoyed degrees, I. Mean. I think the answer is yes it is gonna exacerbate that, problem and. It's a good problem. To have it's, it's you know what Karla said before it, doesn't stop, the. People who. We're already gonna be coming into the major which is continuing, to grow it's not going to stop them from coming if more other kinds of people come so, that means that the growth is potentially, going to be even even. Larger and I think who. Would who would the from. From Illinois, yeah. Yeah Robin I'm sorry who's, talking about that like. This. Has to happen it. Has to happen and, so we, have to deal with it and get out ahead of it and and. It's. It's a moral imperative that. That, we do this in an equitable way, and and. I think partnering, across disciplines. Is exactly. The way that, we can potentially do this because I know and my institution, there's. Pushback, from, the humanities, worrying. About the number of students who are majoring in computer science and I don't want pushback, from them I want collaboration, with them because, these, students who were training a lot of them are going to go out and influence, what. Happens in the humanities, in the future and we have to make sure we're working with them and educating students in a broad way and thinking. Thinking. About the implications of the computing, that they're going to be doing. Yes. My. Education. We get to a point in which.

As. Far as testing the. Student. Performance. Expected. So. The question has to do it online. Education, then and how, can we be sure, in. Computer science that, the quality, of the education, and the value of the credential, and the, competency, of the students going through it. Matched. Those of campus. Education I. Think. We're well past that a number of universities, you. Know but top. 10 ranked universities, around the world and you know beyond are routinely. Doing fully, online learning for campus Georgia Tech for example, for. His freshman computer science class is giving his students a choice do, the fully online class, on EDX, from, Georgia Tech or do the campus class 60% of the students do that and they get the same number. On their transcript. Similarly. UT. Austin has launched a computer science master's, on EDX a Georgia. Tech has a computer, science degree they. Have an analytics degree on EDX a cyber security degree on EDX from computer science and other departments, where the. Degree that the students get is AI denti-cal. To the campus degree so. If you just see a student running around with Ava masters, this diploma, this piece of paper from, some of these universities, it is no different from the, degree students get on campus and so, I think they're well past the point where, we have to worry that the quality, of the assessments, the quality, of virtual proctoring and other techniques we, have well past those. Issues. From. The court from the corporate standpoint I. Think. The, you. Know corporates, are clamoring, for more computer science graduates, and not, only are there looking for a graduates. Come out of these degrees many of them are funding the students to go get the degrees they're, also clamoring, for micro-credentials. Many. Of the corporates are not able to send off their students for a masters they want micro credentials and I think the challenge is there how do we get the corporates to. Appreciate. And recognize. The. Newer micro credentials as opposed, to the older. Form large degrees I think that remains a challenge but as far as some things a degree there's. No difference in the piece of paper that they get so the corporate does not know it's online or on campus today so, Dimitri fire if I could add to first and.

Partly. Agree and partly disagree is my great colleague and I got Ragini Amin to keep them from hitting me so thank you know any, chair I. Know I'm worried look. I agree. With them not in terms of what you acquire, from, the classes, you take online I mean, at MIT we talk about our online classes, or MIT hard they're not any different than the things we do it's really important, that that quality, is there and I really agree that that acquisition which is why I think the micro masters work so well a place. Where I think many of us though are still uncertain, is you, know an undergraduate, education. Is also about other things you learn in, other places it's it's on an athletic field, it's in a drama club it's in it's in a dorm room it's or you know wherever and that's. The place where I think universities have to wrestle with what, is it that that is adding to the degree and. How do you know for online that the credential, is important, but that's about the knowledge there's. This other part of an undergraduate degree that I don't think we want to lose we ought to think about that and, the reason, I raised it as an online I think there's a lot of progress but the notion of forming, communities, to talk you. Do that in a fraternity or a sorority or, a dorm room if you're on a campus online, it's, not yet, quite the same experience, and we have to think about how to provide that I. Would. Like to continue in the discussion asking all of you the following question oh you wanted to add, something to that actually want to ask Eric question, then rather than turn the challenge around about saying well what about off, campus students what about now the on campus students right what about the challenge, of providing. Them as a brick-and-mortar place. Where if where students are just there, what. Is it that we do that makes it better than consuming, it online or sitting, in a lecture, you know is it active learning is that the you mentioned the co-curricular, activities, but what about things that happen in the classroom maybe a different classroom yeah so I mean, my reaction, is I think. In. The classroom, some of it is mentoring, some of it is again as connections I mean how to admit when I teach a big class I hate it when they're talking in class so I'd rather they do it outside of it but I think on campus, it's it's two things one it's.

Being, Able to build the connections, to have discussions, afterwards, yeah that that, you you get by being, on campus, the. Other one and I feel guilty saying it because I don't mean to it don't mean it to apply to me but but one of the advantages of doing. It on campus and one of the advantages of still, having lectures, I mean I'm mixed on this is you. Get, to see role models I'm, not one but, you get to see role models you get to see mentors, that you say oh that's, cool I mean I think when it comes to diversity that's, an important part of who are those role models and, my, experience is it's not the same as watching a video somebody as actually. Being in the classroom going, wow that's. A Nobel laureate that's. Giving that lecture yeah that's, cool I think I agree with most of what Eric said but I'll just give you a statement as to. Today's. Generation, of students is different my daughter, the sophomore at MIT her. Biggest superstars, her. Biggest role models, are not people I wish it was me are. Not physical, people how. Many of you heard of the green brothers. These. Are spectacular, youtubers. They. Can put any professor, I mean that's spectacular, creators. She. Goes you know she ended up going for some major. Green brothers conference, or something just so she could be in a crowd of 20,000. People screaming and, it wasn't a rock star concert, it was educators, and and so you can, have people. Motivate, you and inspire you online. As much as in person I think the, physical reality I think sometimes is not as good as the virtual reality, so. You knew where it's gonna be a discussion here right and so not and I are doing this really well thank you I have experience, with both you, had flipped classrooms, what, was your experience with. Using, both media. Both way online as well as he. The. Our, you. Know experience. In classrooms, one of the reasons that I stopped teaching 603, six it's. Because you know we had like I don't know 400 students. In the class, so given. This huge class when you don't know your students, and, you, really cannot have a discussion I'm. Not. Sure that we're really delivering, the goods that's. Why and also I kind of felt that I am teaching to everybody and nobody. Bored. In the classroom because they knew it and there were people who really couldn't follow, so. I think that, the future is actually in combining, the, two and finding. Certain things that can be done online especially, teacher may be very technical stuff where people need different you. Know kind of personalized, approaches, and then, find a way to break, up these big classes and really give the value to our students, of having the discussions, and I was so happy I just came teaching my the, new class and it was really fun and we had really. Extensive discussion but I know that next year when it's gonna be instead of 90 it's. Gonna be 250. We cannot have the discussion, so I'm reading it as MIT.

And, Other institution. But computer science grows to. Think what is the most effective way of combining, the, technology so. We do the best utilization. Of human, resources, so, maybe instead of me teaching you know I know 26, or 27 lectures. Maybe, I'm will teach less. Lectures less than recorded, but this lectures will be divided, to subgroups, where we really get to know our students, is Dmytro a really quick comment I I agree, with Regina and. One. Of the, disadvantages. Of a big lecture is, that, I don't know of any undergraduate, who in front of 600 of their closest, friends are going to say professor I didn't understand that you, know so if they miss something there's no reset they do it when they are 60 sorry. But they do it when they are 60 well. They'll. Get closer it's okay yeah but my point about it is one of the advantages about him flipping the classroom and putting the lectures online is. That a student will go back and re-listen to it the other advantage, quick, story my older son of my took my MOOC. Really. Bad dinner, discussion you. Know why the hell did you do it look great they got yes, I will separately, by. The way my wife is is the head of the computer science department of Wellesley and MIT PhD so I don't know what the hell she was doing taking this class I want. Five here the, reason I wanted to tell you this story was because, one of the things I discovered from, both of them which i think is interesting about, putting the lectures online they. Would thanks. To EDX they would mostly, listen, to the lecture at one-and-a-half speed which. They also thought was hilarious you can do that until. They got to art, until, they got to a hard part of the class and then, they slowed down to 3/4, speed the point is you give the student more control, of what. Do I listen to how quickly do I go through it and I think the flipped classroom, that's, an inte

2019-03-03 10:26

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I’m convinced that this panel discussion will be to education as Feynman’s plenty of room at the bottom was to nano-science. A pleasure to hear such visionaries

Hello World


Wish getting accepted at MIT was possible for humans


hem.. no...

Great speech!


+Giovanni Radianes Second*


dreams: studying in MIT reality: to be going to be studying in useless Turkish universities

Do you teach biology or physics to all? Then what's up with the obsession to teach people computer science? Let us do our thing without that much competition!

Dear MIT, please reply to the message of the Science show (YouTube channel), they'll make a Russian dubbing of your videos. the author of this channel sent you an e-mail with the indicated offer.

Without much competition the field wouldn't advance better, new ideas from different people=advancement. How do you think mathematics, physics, chemistry advanced?

Cut the equality nonsense, the fact of the matter is, the races and sexes are far from biologically equal, this is the primary reason for gaps in achievement. Look into the works of Richard Lynn, Linda Gottfredson, Philippe Rushton, Hans Eysenck, Charles Murray and Arthur Jensen just to name a few. You can also look into the statements of co inventor of the transistor, William Shockley, and co discoverer of DNA, James Watson.

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Slogan of India is " all people of world is our family"

Stupid biological falsehoods in western education being spread around today.


Son geniales amigos un abrazo desde San Jerónimo Antioquia Colombia

they do actually

Same reason they love mass immigration from third world countries. They want to drive wages down so they can increase their profit margins. Increase supply for a high demand job and you can pay less for it.

@Giovanni Radianes Second*


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