3.4 - Crowdsourcing How We Learn

Hi. A few years ago, my friend and colleague Mike Wesch-- a professor at Kansas State University, an anthropologist by training-- crowdsourced with his students in a huge a lecture hall a video called "Vision of Students Today". The video begins with looking at a lecture hall, and looking at what students are looking at on their screens. Believe me, most students are not looking at material relevant to the class: they're playing with their Facebook page, they're emailing, they're on Twitter, they're on Tumblr, they're on Pinterest. All of those things, the screen is just more compelling than many lectures are today. So what Mike did was he asked his students to actually come up to use their roles sitting in a lecture hall, to come up with a simple video that dramatized the role, the vision of students today in a new kind of learning. The video is up on our Coursera page. Please go watch it. It's a very simple video that they made together, beautifully orchestrated, and it drives home the point that we need a more relevant engaged education that engages the mind and hearts of students, not just records their test scores at the end of a class.

"Vision of Students Today" has been viewed by 4.9 million viewers. It clearly speaks to us. I think one reason is because we know the limits of the lecture hall. Lectures are fantastic for inspiration. No one quite knows why, but humans like to be together in groups where we experience things that are elevating together. Whether it's a football game; church; a rock concert; or a lecture hall, as the TED Talks have taught us, people just enjoy being in a situation where everyone laughs together-- comedy clubs would be another thing, another example-- laugh together; enjoy together; emote together. That's why we go to movies as well as watch them on DVD. All of those things are important. On the other hand, we know lectures are pretty core for retention and applicability. The hierarchical method of one teacher talking to hundreds of students is not great for actually learning something that you can retain and apply back later. Ethnographers at famous talks have asked people what they learned in the talk. And even people who leave a talk that say, "It's fantastic," like the most inspiring talk they've ever heard, when asked to paraphrase the content, almost never can do more than about 5 percent of the content. And, when you compare what people remember, there's huge variance, and what people often remember are, not actually what they heard in a lecture, but what is meaningful to them about that lecture and how it relates to their own life. We actually are constantly moving in and out of attention in a lecture hall. We don't know it, unless someone has us hooked up to a scientific experiment, we're not aware that we aren't really paying attention all the time. Sometimes we are. Sometimes we are bored out of our minds and we know very well that time is passing and we're not really engaged with the material.

But the point is that it's not nearly as engaging of our attention as such things as writing; contributing; participating; texting; and doing all those things that, in this class, we've talked about as "See one, do one, teach one, share one". This is why I keep emphasizing that, no matter what we're learning on the videos of this MOOC, the real learning is going to happen when you take these ideas and talk about them with others; talk about them back on blogs; talk about them on the forums; talk about them with some others in this class and with others that you know: teachers, parents, students, friends. Use the ideas. Don't just have the ideas, but actually translate them into the world and use the ideas.

This method of, "See one, do one, teach one, share one" is an old method that comes out of medical school training that we've flipped by adding the "share one" component. And in a sense, that's a good definition of crowdsourcing-- or participatory or connected learning. I've been very, very proud to be part of the MacArthur Foundation's Digital Media and Learning Initiatives, and all of those initiatives are inspired by the idea that we have new ways of learning online and offline-- and how can we use those to make learning social; relevant; meaningful? And, we've, so far, with the Digital Media and Learning Competition's funding, been able to give grants to well over 100 projects in 20 countries. And seeing what people are doing in engaged, interactive ways is very, very inspiring.

Some other examples of crowdsourcing that you might be familiar with are things like reCAPTCHA. reCAPTCHA's those-- they're sometimes annoying-- those things you write in order to get into a website to prove that you're a human and not a robot. Actually, those come from words in books that haven't been machine readable, as the world's books are being digitized so we can have a universal library; there are some images that just are not readable. Those ReCAPTCHAs are actually using your trying to get entry to a website as content to translate a word that the machine can't translate. So it's a machine generated way of humans to translate something that machines can't do. This was invented by a very brilliant computer scientist and engineer, Luis von Ahn-- happens to be a Duke graduate; I have to put that in here-- and Luis has now moved on to a second project called Duolingo. And Duolingo is a variation of crowsourcing. In Duolingo, you can learn a language, and as you're learning the language, you're actually translating web text that machines can't translate instead of See Jane Run or See Spot Run and the kind of typical sentences you use when you're translating. In Duolingo, in order to learn languages, they give you practice sentences, and the sentences they give you to practice on are actual sentences that, for one reason or another, haven't been able to be translated; and they are basically crowdsourcing those translations and using all of us in our desire to learn a new language to actually do translation. They have multiple people translating and then filter out agreements and disagreements.

Another example of crowdsourcing happens to be my favorite-- although it's stopped now, because we finished what we needed to do-- and that's a project called Galaxy Zoo, which crowdsources the identification of objects in deep, deep space. When I was on a book tour a few years ago, I would wile away the time in airports doing Galaxy Zoo; it's kind of like a metaphor of my plane being delayed, so I was helping to identify objects in deep space. And what that Galaxy Zoo would do would be show you photographic image of some object in deep space and then ask you questions about its shape, its configuration, if you saw anything startling. And all of those objects were actually things that professional astronomers had not been able to identify. But by having tens thousands of us giving information about those, we were able to fill out this whole online encyclopedia of objects in space. And we finished the project. Microsoft, which is the host of Galaxy Zoo, has moved onto other projects, because basically there aren't any more of these photographic objects in deep space. I think we did our job; there were enough delayed planes that I and others were able to do our job identifying objects.

Another astonishing crowdsourcing project is Foldit. And this was a game-based project that was about protein growth and reproduction, and trying to figure out the reproductive mechanism of a certain cell that, when it went out of control, basically translated into the AIDS virus. And in a few months, gamers were able to solve a major, major problem in this protein replication cycle that scientists had been trying to work on since AIDS was first diagnosed in the 80's; it was really astonishing.

Wikipedia of course, is the most famous crowdsource project: the biggest encyclopedia the world has ever known, created for free, available for free, edited for free by people like you and me. It's a total non-profit enterprise, 285 languages, millions and millions of viewers, the 7th busiest website on the World Wide Web.

One thing we're finding is that crowdsourcing works, because people-- maybe it's the same thing that makes us want to go lectures-- people like working together for something productive. People enjoy knowing that their contribution matters. It's actually a pretty great view of human nature. We used to think the rational choice of human nature was we paid people to do things. Well we know from crowdsourcing is, actually, people enjoy contributing if they know their contribution is going to make a difference. To me that is the single, biggest component of learning. In other words, if-- in any kind of learning-- you can show kids-- kids of any age, including lifelong learners-- that what they're learning can make a difference in the world, they will eagerly, industriously, learn far more than you learn from just a standard assignment.

On our website, you'll find the work that my own students-- mine and behavioral economist Dan Ariely's own students did-- in a class called "Surprise Endings" that was about the content and the methods of social science and literature. This premise of our class-- Dan is a social scientist and behavioral economist; I'm trained in the humanities-- the premise of our course was that, through experiments-- empirical experiments-- you can find out lots about human nature; and Dan's found out all kinds of things about human nature from his very, very clever and wise experiment. And yet, there are these artists-- visual artists, filmmakers; literally people who don't use any empirical assessments at all-- and manage to come up with equally deep insights to human nature, some of which last centuries and centuries and even translate across cultures. How is that possible that people have those intuitions?

We not only taught this in a dialogic class. We had our students create the syllabus, we came up with about 7 topics: self-control, racism, gender identity, relativity, honesty & dishonesty-- and lots of other key topics. And we had our students set up a syllabus. They would interview us in class-- and those video interviews were put up on the website-- and then in project teams of 4, they created their own learning modules about each of those topics. So they took-- basically, what we talked about in our lectures-- what they learned about in their own materials and created a public course, just out there for the public good that anyone can learn about it. And this week I would like you to made sure you visit that "Surprise Ending" site, so you can see the work that students-- totally on their own-- created just for the public good. They put in far, far more time than any students would have in another class. Instead of writing the usual writing the term paper the night before it's due, my students met on average of 10 separate times-- totally self-organized-- in small groups to work on their projects outside of the class time. And I think most of them ended up saying that it was one of the most fulfilling things they'd ever done. Why? Because they were controlling the topic. They were controlling the product, and doing something in public. It wasn't just a busy work exercise for me and Dan, the teachers, to read. It was something that's out there on the web for the public that anybody can learn from. And there's something about that. Call it altruism. Call it our desire, all of us, to teach and lecture others. But there's something about being able to translate what you know in a way that somebody else can learn it that seems deeply profoundly optimistically human.

Do MOOCs do that? I'm not sure. But one thing that excites me about MOOCs is it's putting new idea out there and it's inspired other ideas. In the fall of 2013, many of my colleagues contributed to something called a DOCC; not a MOOC but at DOCC: a distributed online collaborative course, where many, many people around of the U.S. and abroad were teaching classes on feminist theory and women in technology. A group
calling itself the FemTechNet put these classes on and allowed the students to collaborate with one another. Simultaneously, with this Coursera course, about 40 different professors around the world are teaching face-to-face versions of some aspect of the history and future of higher education. Our students are also taking the Coursera class, so they are your colleagues and your co-students and your peers online. But they're also talking about what we could learn face to face. What we can learn by this distributing way of communicating across different institutions, what we can learn on our own, what we can learn peer-to-peer, and what we can learn in MOOCs: all of this is about learning the future together.

Learning the future together-- you can see my little HASTAC button-- that's the model of an organization that I co-founded with other scholars across many, many fields in 2002. We now have about 12,000 members. HASTAC is a long acronym-- H-A-S-T-A-C-- and it stands for "Humanities, Arts, Science, and Technology Alliance and Collaboratory". The alliance is made of many institutions, many individuals, there's no prerequisite, it's free; we're all working here. The collaboratory is because we believe that ideas are formed best through collaboration. And like a laboratory, nothing is final. The whole point of a collaboratory is you're working together towards ideas. You're not by any means saying, the idea I have now, whatever now is, is the final answer. In fact, I would say that one thing we learn in every collaboratory is that knowledge is always changing. Some knowledge is eternal, some knowledge is the same; sometimes it's learning like it's 1992. Sometimes it's Back to the Future.

Thank you for staying with us so far. These first three lessons have been about the history of higher education, a history that's an activist history designed to help us face the future of higher education. That's what comes next: the next three segments will all be devoted to new paradigms for mostly higher education, new ways of learning the future together. Bye, take care.