What Can MOOCs Teach Us About Learning?
Here is what I find breathtaking about MOOCs: for the first time in human history, we have the means to teach hundreds of thousands of people around the world who would not otherwise have any chance of an access to the kinds of specialized subjects offered by higher education, a form of learning formerly reserved largely for the affluent (as nations, as individuals) or at least the fortunate (those living in countries that support/subsidize higher education and make it available at a low enough cost to be accessible beyond the 1%). The potential for a true Web-based interchange of knowledge, at a time of such momentous change, is astonishing. John Seely Brown calls this a "Cambrian moment," a time when small changes can have astonishing results because the paradigms themselves are in a process of transformation: lhttp://www.johnseelybrown.com/stanford2011.html MOOCs can be part of that transformative, epoch-making potential that began in April 1993 when the Mosaic 1.0 browser became available to the general public and, for the first time in history, anyone who had an idea could communicate that idea, instantly, to anyone else in the world who had access to the World Wide Web. Take that in. Breathtaking.
Here is what I find depressing about MOOCs: so many of them are talking heads on a screen. I mean, really? That's the best we can do in 2012? All the research shows that the single least effective mode of learning is from the lecture. It's least effective for retention and it's vastly less effective than experiential, project based learning when it comes to having subsequent applicability to new situations, to application beyond the final exam. The one thing that the great lecture is good for (and remember, this is only the great lecture) is inspiration. Humans are social animals and we like being inspired together--in church, at football games, at concerts, movies, plays, in live tv audiences, and in a great lecture. We simply learn something about the human community as well as about the content of what we are watching together by all being in a large space oohing and aahing together, clapping our hands or singing in one voice, shouting or jeering, laughing or nodding our heads in appreciative insight and knowing. We almost all have great lectures and lecturers in our past who said something to us, when we were there in the crowd, that felt as if it were speaking directly to us, alone, touching our hearts, changing our minds, inspiring our soul. The Talking Head version of the MOOC robs the great, mass lecture of exactly that experience of community that is its power.
Here is what I find hopeful about the future of MOOCs: We are taking baby steps with the medium right now, and, fortunately, a lot of dedicated, earnest, serious thinkers are asking what MOOCs can teach us about learning so that these first steps will help us taking gigantic, important leaps in the future. We are collecting the data, keystroke by keystroke, that will help us understand more and more about what modes of learning work in what situation and for whom. We will soon know more about what motivates students to stay in a course, what makes them drop (the MOOC drop out rate tends to be very high), what motivates them to learn in the first place? What motivates them to form peer discussion groups, online or off, around course content? How many go from an introductory course to a deeper one--and why? In other words, the quantity of data and the increasing sophistication with which we, aided by the machine, can read and analyze and parse and visualize data, means that we are learning more about the minutia of learning now than we have ever known before. If we get over the hype of the MOOC at this moment, if we can think about this as an initial foray into a major breakthrough in knowing how we know, in metacognition, great new forms of interactive learning are possible.
Here are some assumptions I'm making about why we need MOOCs and what we might learn from them:
(1) Even great teachers often know more about what of their "tricks" works than we know how and why they work and for which students. Like a great stand-up comedian who uses feedback from the audience at each and every gig to hone timing and punchline, a great teacher learns how to have impact. But impact is not the same thing as deep learning of the kind that gives the learner the ability to analyze other problems, even ones with very little seeming relationship to the first, and make appropriate decisions. World-building, is what JSB calls it. I work very hard at my teaching. It has taken me the last decade of extreme classroom experimentation for me to understand that my finest moments as a teacher may live on in the memory of my students (they often write me and tell me so, after all, as they also do on year-end evaluations), may be inspiring to them lifelong (as such moments in my student life have also been and continue to be for me), but they are not the cognitive tool kit that teaches them how to make the key decisions in the rest of their lives. World-building. I need to be proud here of the many students I've trained. I need to be humble about how little I actually know about what of the many aspects of our relationship of mentor-mentee helped some of them succeed, some not, and what makes the difference. Maybe the real moments that helped then in the kind of profound learning that changes a life were when I was in the mentee role (I'd bet on that one, actually). Maybe the real moments of true learning happened not when I was most brilliant but when I was most confused and uncertain--and they stepped in with the right answer (and that one too). (Put that pedagogical insight into your MOOC and smoke it!)
(2) Teachers are no different than any other human. It is hard to break down exactly which pedagogies work best because, as humans, we are not very good at seeing beyond our own assumptions, cultural or personal. We believe we see the world but, in order to pay attention, in order to focus, we are actually screening out enormous amounts of "noise" (i.e. information we do not think is important to our focus at that time) all the time. When you are teaching, you are expending an enormous amount of energy on your craft--which means you are screening out an enormous amount of energy. Some of what you are screening is the actual feedbck, in the moment, from your students, about your teaching, about their learning. Is it the powerful metaphor that creates the "aha!" moment? Is it the compelling story? Or is it the gesture you made while telling the story (I suddenly flashed on the way Lena Horne would sing a note, deliberately and every so slightly off key, a little sharp, and at the same time crumple her blouse over her heart and the word, at that moment of clutching dissonance would touch you too)? Second by second, it is almost impossible to know what communicates, what touches, what reaches. But we have machines now that can read video, read keystrokes, and tell us exactly what we cannot see.
(3) It is ridiculous to think that MOOCs should only be about teaching skills. If there is one thing that separates lower from higher forms of learning--the metacognitive kinds that prepare you for bold decision-making in times of radical and even catastrophic change--it is that lower learning is skills-based whereas metacognition is always about text, context, culture, emotion, situation, introspection, theory, practice, design, imagination, power, practice. In other words, learning a skill allows you to practice that skill when someone else assigns you a task to perform. Learning how to think about the acquisition of skills relative to the requirements of the situation you are in allows you to become a leader, a decision-maker. Art, philosophy, music, anthropology, literature, games, surprise, storytelling, magic, suspense, language, sociology, political theory, geography, history . . . all those are as basic and important to metacognition as quadratic equations, Python, human-computer interaction, or other high level scientific, technological acquisition. Each, learned in the context of the other, is not only a skill but an entry way into a system of learning and, if it is done right, a system that you have the power to modify according to the demands ahead.
Do MOOCs today teach us about learning? Not yet. But they have the potential if we ask the big, right questions. Do MOOCs work? What value do they add and for whom? How do they add value? Do they supplement other forms of learning or substitute? Do they replace the classroom or prepare for it? If they prepare for the classroom, how can they help us transform it? What new can the performance of hundreds of thousands of online students tell us about motivation--especially the motivation to learn versus the motivation to be certified? The resting MOOC cheating scandals are a symptom of the confusion we're now making between learning and certification. Both are valid, for different reasons, but, if we confuse them, then we incentivize cheating. That is not a good thing, for society, for learning, for individuals who, ultimately, cheat themselves: certification will get you a first job, it won't help you succeed in that job because you will not only not have the basics (i.e. you cheated, you didn't learn), but you will have the false practice of thinking sneaking by is how you succeed. You will get caught the first (or third or fourth) time you have to produce something substantial and there's no one beside with you from whom to filtch the right answer.
These are big, philosophical questions. And we need to be asking them, demanding answers. We don't want to be teaching in the worst possible way to the most possible people. We want to be learning the best ways to teach by doing careful, open-ended and open-minded research on exactly how massive numbers of people are learning online.
Sebastian Thrun, CEO of Udacity and the person who taught the first headline-grabbing MOOC when his online Artificial Intelligence (AI) course at Stanford unexpectedly drew 160,000 students, has said that right now is Dartmouth 1955 for online learning. http://en.wikipedia.org/wiki/History_of_artificial_intelligence The Dartmouth Conference held in the summer of 1956 brought together an array of junior and senior scholars who, together, thought about artificial intelligence and, for all intents and purposes, created the field together by asking the unanswerable, tough, demanding, deep, principled, important, bold, courageous questions. They were not asking silly and inevitably disappointing questions of the variety now being asked of MOOCs (i.e. can MOOCs bring down the cost of higher education, an apples and oranges conundrum if ever there was one). Wikipedia tells us of the Dartmouth Conference: "The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain." Here's another great sentence from that entry: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore."
Ponder that one! The project of AI was bigger, bolder, more circuitous than anyone imagined. Even know, when something is useful enough, it's not labeled AI. That's my hope for the future of the MOOC. It's not MOOCs anymore. And it's not any longer some silver bullet that will "cure" the problem of the high cost of contemporary institution-based universities. If we ask the big, complex, hard and thoughtful questions, MOOCs, like AI, won't be the label. The label will be, quite simply: making the best possible forms of learning accessible to the most possible number of people.
Cathy N. Davidson is co-founder of HASTAC, a 9000+ network committed to new modes of collaboration, research, learning, and institutional change. Along with a steering committee of scholars across many fields, Davidson has been directing HASTAC's operations since 2006, when www.hastac.org moved to Duke University, where she also co-directs the Ph.D. Lab in Digital Knowledge. She is author of The Future of Thinking: Learning Institutions for a Digital Age (with HASTAC co-founder David Theo Goldberg), and Now You See It: How the Brain Science of Attention Will Transform the Way We Live, Work, and Learn (Viking Press). She is co-PI on the HASTAC/MacArthur Foundation Digital Media and Learning Competitions. NOTE: The views expressed in Cat in the Stack blogs and in NOW YOU SEE IT are solely those of the author and not of HASTAC, nor of any institution or organization. Davidson also writes on her own author blog, www.nowyouseeit.net . The paperback of Now You See It was published July 31, 2012 : http://tinyurl.com/bqquoaz