Posts Tagged 'Udacity'

MathThink MOOC v4 – Part 8

In Part 8, I explain why I believe MOOCs cannot and will not lead to cost savings in higher education – at least in a nation that values its standard of living.

As I’ve noted in previous posts to this blog, for the first version of my Introduction to Mathematical Thinking MOOC, I took the first part of a course I had given many times in regular classroom settings, and ported it to a MOOC platform in what I thought was the most sensible way possible. In particular, I changed only things that clearly had to be changed. It was always going to be an iterative process, whereby each time I gave the course I would make changes based on what I had learned from previous attempts.

Given the significant differences between a physical class of 25 entry-qualified students at a selective college or university and a distributed class of 80,000 students around the globe (the size of my first MOOC class in Fall 2012), of widely different educational backgrounds and ability levels, for whom the only entrance criterion was being able to fill in a couple of personal information boxes in a Website, it made sense to maintain – for the first version – as much as possible the contents and structure of the original classroom course. That way, I could focus on the MOOC-specific issues.

After the first session was completed (survived more accurately describes my sensation at the time), all bets would be off, and I would follow where the experience led me. I felt then, and continue to feel now, that there is no reason why a MOOC should resemble anything we are currently familiar with.

I watched as Sebastian Thrun quickly moved Udacity away from his original conception of a highly structured, programmed traditional course – with all that entails – to offering more a smorgasbord of mini-courses, built up from what can be viewed as stand-alone lectures. I asked myself then, and continue to do so, if I should hang on to the central notion of a course, and maybe just tweak it.

So far I have decided I should, the main reason being, as I tried to explain in my last post, the kind of experience I feel best results in the kind of learning I want to provide.

In particular, the primary goal of my course was, and is, to help develop a particular way of thinking – certain habits of mind. That is best achieved, I believe, by focusing on particular “content”.

I used the quotation marks there, because I think it is not accurate to view learning experiences (for experiences are what produce learning) as a certain volume of “content” that is “contained” is some sort of container or vessel. But it seems that everyone else knows what the term (educational) content means – a shared understanding that provides Silicon Valley entrepreneurs with a nice story to raise investment for developing “platforms” to “deliver” that “content” – so I’ll go with it. (I used the word five times in my last post, and no one wrote in to object or say they did not understand what I meant.)

Anther reason for maintaining a course structure (the indefinite article is intentional) is that I want my course to function as a transition course, to help students make the shift from high school to university. And for the foreseeable future, I think universities will continue to carve up “content” into delivery packages called “courses”.

The third reason for having a course is our old friend, student expectations. Many of my full-term students tell me that they signed up because they want a course, with all that entails: commitment, deadlines, testing, and community.

That third reason likely reflects the self-selection implicit in students who sign up for a MOOC, fully 80% of whom (according to recent MOOC research) already have a college degree, and hence are adapted to – and good at – learning that way.

This implies that, by offering a course, I may be reinforcing that emergent trend of primarily providing further college education to individuals who already had one.

That may, in fact, be where MOOCs will end up. For sure, Udacity’s recent pivot appears to reflect Sebastian Thrun’s having decided to direct his (investors’) money toward that audience/market.

If the provision of continuing higher education  for college graduates does turn out to be the main benefit that MOOCs provide, that will surely be something for we MOOC developers to be proud of, particularly in a world in which everyone will need to learn and re-tool throughout their lives. (Major innovations rarely land where the innovators thought they would, or do what was originally intended.)

But in that case, MOOCs won’t yield the massive cost savings in first-pass, higher education that many politicians and education-system administrators have been thinking they offer.

In fact – and here I am probably about to bring the wrath of Twitter onto me – I think the current goal of “solving the problem” of the rising cost of higher education by finding ways to reduce it, misunderstands what is going on. I suspect the costs of providing first-pass higher education will continue to rise, because quality higher education is becoming ever more important for life in the Twenty-First Century.

Just as the introduction of the automobile meant society had to adjust to the new – and ever rising – expense of gasoline, so too the shift to knowledge work and the knowledge society means we have to adjust to the cost (high and rising) of a first-pass higher education (the fuel for the knowledge society) that stays in synch with society’s needs.

What MOOCs and other forms of online education have already been shown to be capable of – and it is huge – is provide lifelong educational upgrades at very low cost.

But based on what I and many of my fellow MOOC pioneers have so far discovered – or at least have started to strongly suspect – the initial “firmware” required to facilitate those continual “software” upgrades is not going to get any cheaper. Because the firmware installation is labor intensive and hence not scalable – indeed, for continuously-learning-intensive Twenty-First Century life, not effectively scalable beyond 25-student class-size limits.

The world we have created simply entails those (new and rising) educational costs every bit as much the growth of the automotive society meant accepting the (new and ever-after rising) cost of automotive fuel.

(Oh, and by the way, we in the US need to realize that the knowledge society requires better teacher preparation in the K-12 system as well. Well-educated humans are the new fuel, and they neither grow on trees nor are found underground.)

Okay, that’s enough editorializing for one post. At the end of my last report, I promised to describe how I structure my course so that, while designed primarily to provide a framework for a community learning experience, it can still be useful to folks who want to use it as a resource.

First, what do I mean by “resource”? I decided that for mathematical thinking, it was not possible to produce Khan Academy style “online encyclopedia” materials, where someone can dive in to a single video or narrowly focused educational resource. You simply have to devote more than ten minutes to gain anything of value in what I am focusing on.

So I set my sights on people who come in and complete one or two “Lectures”, a Lecture in my case comprising a single thirty-minute video and some associated problem-solving assignments. So I am not delivering “bite-sized learning.” I am serving up meals. (Restaurant meals, where you have time to savor the food and engage in conversation.)

To facilitate such use, the earlier Lectures focus on everyday human communication, ambiguity resolution, logical reasoning, and very basic mathematical ideas (primarily elementary arithmetic – though in a conceptual way, not calculation, for which we have cheap and efficient machines).

Only in Weeks 7 and 8 do I cover more sophisticated mathematical ideas. (Weeks 9 and 10 comprise my new Test Flight process, which I described in Part 6 of this series. That part is specifically for advanced mathematics seekers.)

Thus, Weeks 1 through 6 can be accessed as a resource by someone not strongly interested in mathematics. At least, that is my current intention.

Admittedly, someone who delves into, say, Week 4 might find they need to go back and start earlier; but that’s true of Khan Academy as well, and is surely unavoidable.

By making the awarding of a Statement of Accomplishment dependent on completion of the Basic Course (first eight weeks), not the achievement of a particular grade, I hope to be able to maintain and reward the participation of someone who begins by just “trying out the course” and gets hooked sufficiently to keep going.

To cater for this dual use as much as possible, in addition to changing the course structure, the upcoming new session has four new videos, and I modified four existing ones. (All the time keeping that magic ingredient “content” the same.)

Well, that’s where I am at present. As I noted earlier, this blog series is essentially my lab book – complete with speculative reflections – made public in real time. (I am already deviating from things I said in this blog just a year ago.)

Ah yes, last time I also promised I would say “what motivated me to give a MOOC in the first place – and still does.” The answer is, “Reaching students who do not currently have access to quality higher education.”

That probably seems very much at odds with everything I’ve said above. It’s not. I’ll explain why in my next post.

MathThink MOOC v4 – Part 2

In Part 2, I reveal that I share with Steve Jobs, J K Rowling,  Sebastian Thrun, Thomas Edison, and a successful Finnish video-game studio head, a strong belief in the power of failure.

This post continues the one posted two days ago about the expectations students being to my MOOC.

One of the problematic expectations many students bring to my course is that I will show them how to solve certain kinds of problems, work through a couple of examples, and then ask them to solve one or two similar ones. When I don’t do that, some of them complain, in some cases loudly and repeatedly.

There are several reasons why I do not simply continue to serve up the pureed (instructional) diet they are familiar with, and instead offer them some raw meat to chew on.

Most importantly, the course is not about mastering yet more, specific procedures; rather the goal is to acquire a new way of thinking that can be used whenever a novel situation is encountered. Tautologically, that cannot be “taught.” It has to be learned. The role of the “instructor” is not to instruct, but to offer guidance and feedback – the latter being feasible in a MOOC by virtue of most beginners having broadly similar reactions and making essentially the same mistakes.

To progress in the course, the student has to grow accustomed to the way professional mathematicians (to say nothing of engineers, business leaders, athletes, and the like) make progress: learn by failing. That’s the raw meat I serve up: failure.

Not global failure that debilitates and marks an end to an endeavor; rather repeated local failures that lead to eventual success. (Though the distinction is really one of our attitude toward a failure – I’ll come back to this in a moment.)

Most of us find it difficult making the adjustment to regarding failing as an integral part of learning, in large part because our school system misguidedly penalizes (all) failures and rewards (every little) success.

Yet, it is only when we fail that we actually learn something. The more we fail, the better we learn; the more often we fail, the faster we learn. A person who tries to avoid failure will neither learn nor succeed. If you take a math test and score more than 75%, then you are taking a test that is too easy for you, and hence does not challenge you to learn. A score of 75% or more says you did not need to take the test! You were not pushing the frontiers of your current abilities.

I should add that I am not talking about tests and exams designed to determine what you have learned, rather those that are an integral part of the learning process – which in my case, giving a course that offers no credential, means all the “graded” work.

In my course, the numbers the system throws out after a machine-graded Problem Set, or the mark assigned by peer evaluation, are merely indicators of progress. A grade between 30% and 60% is very solid; above 60% means you are not yet at the threshold where significant (for you) learning will take place, while a score below 30% tells you either that you need to put more time and effort into mastering the material, or slow down, perhaps working through the remainder of the course at your own pace then trying again the next time it is offered. (Another great advantage of a free MOOC.)

What is important is not whether you fail, but what you do as a result. As I was working on this post, I came across an excellent illustration in an article in FastCompany about the Finnish video game studio Supercell. Though the young company has only two titles in the market – Clash of Clans and Hay Day – it grossed $100 million in 2012 and $179 million in the first quarter of 2013 alone.

Supercell’s developers work in autonomous groups of five to seven people. Each cell comes up with its own game ideas.  If the team likes it, the rest of the employees get to play. If they like it, the game gets tested in Canada’s iTunes App store. If it’s a hit there it will be deemed ready for global release.

This approach has killed off several games. But here is the kicker: each dead project is celebrated. Employees crack open champagne to toast their failure. “We really want to celebrate maybe not the failure itself but the learning that comes out of the failure,” says Ilkka Paananen, the company’s 34-year-old CEO.

It’s not just in the PISA scores where Finland shows the world it knows a thing or two about learning; you can find it manifested in the App Store download figures as well!

(And let’s not forget that another Finnish game studio, Rovio, produced over a dozen failed games before they hit the global App Store jackpot with Angry Birds.)

Where I live, in Silicon Valley, one of the oft-repeated mantras is, “Fail fast, fail often.” The folks who say that do pretty well in the App Store too. In fact, some of them own the App Store!

One of my main goals in giving my MOOC is helping people get comfortable with failing. You simply cannot be a good mathematical thinker if you are not prepared to fail – frequently and repeatedly. Failing is what professional mathematicians do maybe 99% of the time. Responding appropriately to failure is a key part of mathematical thinking.

And not just mathematical thinking. It’s definitely true of engineering as well. Remember Thomas Edison, who on being asked how he motivated himself to continue his efforts to build an electric light bulb when a thousand attempts had failed, replied (paraphrase), “They were not failures, I just found a thousand ways it won’t work.”

The metaphor I use regularly in my MOOC is learning to ride a bike. If you think about it, you don’t learn to ride a bike; you learn how not to fall off a bike. And you do that by repeatedly falling off until your body figures out how to avoid falling.

Incidentally, the fact that you really did not learn to ride a bike by learning how to is indicated by the fact that almost no one can correctly answer the question, What direction do you turn the handlebars in order for the bike to turn to the right? Your conscious mind, the one that would have been involved if you had learned how to ride a bike, says you twist the handlebars to the right in order to turn the bike to the right. But, if you are able to ride a bike, your body knows better. You turn the handlebars to the left in order to make the bike turn to the right. Your body figured that out when it learned how not to fall down.

Don’t believe me? Go out and try. Make a conscious attempt to turn right by twisting the handlebars to the right. Most likely, your body will prevent you carrying through. But if you manage to over-ride your body’s instinct, you will promptly fall off. So please, do this on grass, not the hard pavement.

Not surprisingly, six weeks in a MOOC is woefully little to adjust to the professionals’ view of failure. The ones who breezed through my course, unfazed by seeing the system return a grade of 30% on a Problem Set, were in most cases, I suspect (and in a fair number of cases that suspicion was confirmed), professional engineers, business people, or others with a fair bit of post-high-school education under their belts. Those for whom the course was one of their first ventures into collegiate education, often had a hard time of it. (Not a few gave up and dropped the course, sometimes leaving an angry, departing post on the class forum page.)

It’s not called a “transition course” for nothing.

I’ll continue this theme of dealing with student expectations in my next post.

Meanwhile, I’ll leave you with three more examples about the power of failing in the learning process.

The first is Steve Jobs’ 2005 commencement address at Stanford.

The second is J. K. Rowling’s 2008 commencement address at Harvard.

Finally, and very close to home, is Sebastian Thrun’s recent business pivot of his MOOC delivery company Udacity, which I discussed in a commentary in the Huffington Post. Though I would agree with the many commentators that his initial attempt had “failed,” where the tone of many was dismissive, I saw just another instance of someone on the pathway to (for him, yet another) success. It’s all about how you view failure and what you do next.

I’ll continue the theme of dealing with student expectations in my next post.

The MOOC Express – Less Hype, More Hope

A real-time chronicle of a seasoned professor just about to launch the fourth edition of his massively open online course.

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Last week, I headed off to Arlington, Texas, to participate in a large, international conference on MOOC education, part of the Gates Foundation funded MOOC Research Initiative (MRI). While the founders of the big, massively-funded American MOOC (“MFAM”) platforms Coursera, edX, Udacity, and Novo Ed capture most of the media’s attention, this conference was led by the small band of far less well known Canadian online-education pioneers who actually developed the MOOC concept some years earlier, in particular George Siemens and Stephen Downes who organized and ran the first MOOC in 2008, and David Cornier who forever has to live with having coined the name “MOOC”.

(There were so many Canadians in Arlington, they brought their own weather with them, as you can see from the photograph. The conference ended with participants having to change flights and book additional nights in the conference hotel, as a severe ice storm hit the area. With a return flight that happened to lie within a brief lull in the storm, I managed to get out on time, though only after a slip-sliding taxi ride at a snail’s pace to get to DFW Airport. Others had it a lot worse.)

While teams of engineers in Silicon Valley and Cambridge (MA) are building out MOOC platforms that provide huge opportunities for massive scale-up, the two hundred or so researchers and educators who came together in Texas represent the vanguard of the educational revolution that is underway. If you wanted to know what MOOC learning might look at in a few years time, you would have better spent your time at the University of Texas in Arlington last week rather than in Silicon Valley. In his October announcement of the conference, organizer Siemens described it as “the greatest MOOC conference in the history of MOOCs,” a bit of satirical hype that is almost certainly true.

You need both, of course, the technology to reach millions of people and the appropriate, quality pedagogy. For example, the movie industry required a series of major advances in motion picture technology, but fancy film cameras alone are not what gave us Hollywood. As the technology advanced, so too did the art and craft of motion picture writing, acting and directing. Similarly with MOOCs. The focus in Arlington was on the educational equivalent of the latter, human expertise factors.

To pursue the movie analogy a bit further (and with that great spoof movie poster as a visual aid, how could I resist?), the MOOC action that gets reported in the Chronicle of Higher Education and the breathless (but hopelessly off-base and over-hyped) prose of Thomas Friedman in the New York Times is the equivalent of taking an early movie camera into a theater and recording what happens on the stage.

If you want to see the future of MOOCs, you need to hang around with the instructors in the lesser known, small universities and community colleges who, for many years, have been experimenting with online learning. Most of the leaders of that loosely knit band could be found in a large, cavernous room in Arlington for two days last week – along with key figures from such new-MOOC, Ivy League players as Stanford, MIT, and Georgia Tech.

What was the take-home message? In my case, and I suspect everyone else’s, confirmation that we really don’t know where the MOOC train is taking us. The problem is not an absence of good ideas or useful leads; rather the opposite. Don’t expect a “Conference Proceedings” volume any day soon. The best summary you will find is probably the conference Twitter stream (hashtag #mri13).

The fact is, there isn’t even a clear definition of what a MOOC is. The common classifications of c-MOOC (for the original, Canadian, connectionist animal) and x-MOOC (for the later, scalability-focused, Stanford version) don’t help much, since many (most?) of the MOOCs being developed now have elements of both. Commenting on the lack of a generally accepted definition in his welcoming remarks, conference organizer George Siemens opined that it may be that no agreed definition will emerge, and that the term “MOOC” will be similar to “Web 2.0″, remaining an undefined term that “reflect[s] a mess of concepts that represent foundational changes that we don’t yet understand, can barely articulate, but that will substantially impact the system.”

Actually, I should modify my remark above that Stanford is a MOOC player. That’s not really accurate. Some Stanford scholars (including me) are developing and offering MOOCs, but the main focus at my university is research into learning in a digital age, including online learning. There is a lot of such research, but MOOCs are just one part of it. And those MOOC platform providers you keep reading about, Udacity, Coursera, and Novo Ed? They are all private companies that span out of Stanford. They are now (and  were from their creation) Silicon Valley entities, outside the university. Stanford’s original, in-house MOOC platform, eventually called Class2Go, was recently folded into edX, to be run by MIT and Harvard as an open source platform.

As the MOOC research train goes forward, don’t expect the big, Ivy League universities to exclusively dominate the leading edge of the research. The reason so many participants in the Arlington conference came from far less wealthy, and often smaller institutions is that they have been developing and using online education for years to cater to their geographically-diverse, economically-diverse, and education-preparedness-diverse student bodies. The connections made or strengthened at the Arlington conference are likely to result in many collaborations between institutions both big and small, from the wealthy to the impoverished. The Digital World is like that. When it comes to expertise, today’s academic world is just as flat as the economic one – as Siemens clearly realized in drawing up his conference invitation list.

Expect to see MOOC pioneer Stephen Downes leading a lot of the action, as the head of a new, $19 million, 5-year R&D initiative for the Canadian National Research Council. Keep your eyes too on Siemens himself, who at the conference announced his move from Athabacsa University in Canada to be a professor in, and executive director of, the  University of Texas at Arlington’s new Learning Innovations & Networked Knowledge (LINK) Research Lab. (So new, it doesn’t have a website yet!) Track conference keynoter Jim Groom, who whiled away the time holed up at snowed-in DWF Airport to draft this summary of the gathering.  And don’t overlook the University of Prince Edward Island, where Dave Cormier and Bonnie Stewart brave the weather of the far North East. There are a whole host more. Check the list of recipients of MRI grants for other names to follow, and remember that this is just the tip of, dare I say it under the circumstances, the iceberg.

And never, ever forget to read the excellent (and highly knowledgable) ed tech commentator Audrey Watters, who was invited to attend the Arlington conference but had a scheduling conflict. New readers interested in MOOCs, start here.

Recent headlines may have given the impression that MOOCs were a short-lived bubble, and the experiment has largely failed. Nothing could be further from the truth. For one thing, even the much reported business pivot of Udacity was a familiar event in Silicon Valley, as I argued in a commentary in the Huffington Post.

As Siemens put it in his conference welcome, “the ‘failure’ of MOOCs is a failure of hype and an antiquated notion of learning,  not a failure of open online learning.”

Coming up for air (and spouting off)

A real-time chronicle of a seasoned professor who has just completed giving his first massively open online course.

Almost a month has passed since I last posted to this blog. Keeping my MOOC running took up so much time that, once it was over, I was faced with a huge backlog of other tasks to complete. Taking a good look at the mass of data from the course is just one of several post-MOOC activities that will have to wait until the New Year. So readers looking for statistics, analyses, and conclusions about my MOOC will, I am afraid, have to wait a little bit longer. Like most others giving these early MOOCs, we are doing so on the top of our existing duties; the time involved has yet to be figured into university workloads.

One issue that came up recently was when I put on my “NPR Math Guy” hat and talked with Weekend Edition host Scott Simon about my MOOC experience.

In the interview, I remarked that MOOCs owed more to Facebook than to YouTube. This observation has been questioned by some people, who believe Kahn Academy’s use of YouTube was the major inspiration. In making this comment, they are echoing the statement made by former Stanford Computer Science professor Sebastian Thrun when he announced the formation of Udacity.

In fact, I made my comment to Scott with my own MOOC (and many like it) in mind. Though I have noted in earlier posts to this blog how I studied Sal Khan’s approach in designing my own, having now completed my first MOOC, I am now even more convinced than previously that the eventual (we hope) success of MOOCs will be a consequence of Facebook (or social media in general) rather than of Internet video streaming.

The reason why I felt sure this would be the case is that (in most disciplines) the key to real learning has always been bi-directional human-human interaction (even better in some cases, multi-directional, multi-person interaction), not unidirectional instruction.

What got the entire discussion about MOOCs off in the wrong direction – and with it the public perception of what they are – is the circumstance of their birth, or more accurately, of their hugely accelerated growth when a couple of American Ivy League universities (one of them mine) got in on the act.

But it’s important to note that the first major-league MOOCs all came out of Stanford’s Computer Science Department, as did the two spinoff MOOC platforms, Udacity and Coursera. When MIT teamed up with Harvard to launch their edX platform a few months later, it too came from their Computer Science Department.

And there’s the rub. Computer Science is an atypical case when it comes to online learning. Although many aspects of computer science involve qualitative judgments and conceptual reasoning, the core parts of the subject are highly procedural, and lend themselves to instruction-based learning and to machine evaluation and grading. (“Is that piece of code correct?” Let the computer run it and see if it performs as intended.)

Instructional courses that teach students how to carry out various procedures, which can be assessed to a large degree by automatic grading (often multiple choice questions) are the low hanging fruit for online education. But what about the Humanities, the Arts, and much of Science, where instruction is only a small part of the learning process, and a decidedly unimportant part at that, and where machine assessment of student work is at best a goal in the far distant future, if indeed it is achievable at all?

In the case of my MOOC, “Introduction to Mathematical Thinking,” the focus was the creative/analytic mathematical thinking process and the notion of proof. But you can’t learn how to think a certain way or how prove something by being told or shown how to do it any more than you can learn how to ride a bike by being told or shown. You have to try for yourself, and keep trying, and falling, until it finally clicks. Moreover, apart from some very special, and atypical, simple cases, neither thinking nor proofs can be machine graded. Proofs are more like essays than calculations. Indeed, one of the things I told my students in my MOOC was that a good proof is a story, that explains why something is the case.

For the vast majority of students, discussion with (and getting feedback from) professors, TAs, and other students struggling to acquire problem solving ability and master abstract concepts and proofs, is an essential part of learning. For those purposes, the online version does not find its inspiration in Khan Academy as it did for Thrun, but in Facebook, which showed how social interaction could live on the Internet.

When the online version of Thrun’s Stanford AI class attracted 160,000 students, he did not start a potential revolution in global higher education, but two revolutions, only the first of which he was directly involved in. The first one is relatively easy to recognize and understand, especially for Americans, who for the most part have never experienced anything other than instruction-based education.

For courses where the goal is for the student to achieve mastery of a set of procedures (which is true of many courses in computer science and in mathematics), MOOCs almost certainly will change the face of higher education. Existing institutions that provide little more than basic, how-to instruction have a great deal to fear from MOOCs. They will have to adapt (and there is a clear way to do so) or go out of business.

If I want to learn about AI, I would prefer to do so from an expert such as Sebastian Thrun. (In fact, when I have time, I plan on taking his Udacity course on the subject!) So too will most students. Why pay money to attend a local college and be taught by a (hopefully competent) instructor of less stature when you can learn from Thrun for free?

True, Computer Science courses are not just about mastery of procedures. There is a lot to be learned from the emphases and nuances provided by a true expert, and that’s why, finances aside, I would choose Thrun’s course. But at the end of the day, it’s the procedural mastery that is the main goal. And that’s why that first collection of Computer Science MOOCs has created the popular public image of the MOOC student as someone watching canned instructional videos (generally of short duration and broken up by quizzes), typing in answers to questions to be evaluated by the system.

But this kind of course occupies the space in the overall educational landscape that McDonalds does in the restaurant business. (As someone who makes regular use of fast food restaurants, this is most emphatically not intended as a denigratory observation. But seeing utility and value in fast food does not mean I confuse a Big Mac with quality nutrition.)

Things are very, very different in the Humanities, Arts, and most of Science (and some parts of Computer Science), including all of mathematics beyond basic skills mastery – something that many people erroneously think is an essential prerequisite for learning how to do math, all evidence from people who really do learn how to do math to the contrary.

[Ask the expert. We don’t master the basic skills; we don’t need them because, early on in our mathematic learning, we acquired one – yes, just one – fundamental ability: mathematical thinking. That’s why the one or two kids in the class who seem to find math easy seem so different. In general, they don’t find math easy, but they are doing something very different from everyone else. Not because they are born with a “math gene”. Rather, instead of wasting their time mastering basic skills, they spent that time learning how to think a certain way. It’s just a matter of how you devote your learning time. It doesn’t help matters that some people managed to become qualified math teachers and professors seemingly without figuring out that far more efficient path, and hence add their own voice to those who keep calling for “more emphasis on basic skills” as being an essential prerequisite to mathematical power.]

But I digress. To get back to my point, while the popular image of a MOOC centers on lecture-videos and multiple-choice quizzes, what Humanities, Arts, and Science MOOCs (including mine) are about is community building and social interaction. For the instructor (and the very word “instructor” is hopelessly off target in this context), the goal in such a course is to create a learning community.  To create an online experience in which thousands of self-motivated individuals from around the world can come together for a predetermined period of intense, human–human interaction, focused on a clearly stated common goal.

We know that this can be done at scale, without the requirement that the participants are physically co-located or even that they know one another. NASA used this approach to put a man on the moon. MMOs (massively multiplayer online games – from which acronym MOOCs got their name) showed that the system works when the shared goal is success in a fantasy game world.

Whether the same approach works for higher education remains an open question. And, for those of us in higher education, what a question! A question that, in my case at least, has proved irresistible.

This, then, is the second MOOC revolution. The social MOOC. It’s outcome is far less evident than the first.

The evidence I have gathered from my first attempt at one of these second kinds of MOOC is encouraging, or at least, I find it so. But there is a long way to go to make my course work in a fashion that even begins to approach what can be achieved in a traditional classroom.

I’ll pursue these thoughts in future posts to this blog — and in future versions of my Mathematical Thinking MOOC, of which I hope to offer two variants in 2013.

Meanwhile, let me direct you to a recent article that speaks to some of the issues I raised above. It is from my legendary colleague in Stanford’s Graduate School of Education, Larry Cuban, where he expresses his skepticism that MOOCs will prove to be an acceptable replacement for much of higher education.

To be continued …

Liftoff: MOOC planning – Part 7

A real-time chronicle of a seasoned professor embarking on his first massively open online course.

It’s been three weeks since I last posted to this blog. The reason for the delay is I was swamped getting everything ready for the launch of my course four days ago, on Monday of this week. As of first thing this morning there are 57,592 students enrolled in the class.

The course was featured in an article on MOOCs in USA Today. It was a good article, but like every other news report I’ve seen on MOOCs, the focus was on the video lectures. Those certainly take a fair amount of time on the part of the instructor (me, in this case), and are perhaps the most visible feature of a MOOC, just as the classroom lecture is the most visible part of many on-campus courses.

For some subjects, lectures, either in-person or on a computer screen, may be a major part of a course. But for conceptual mathematics, which is what my course is about, they are one of the least important features.

Learning to think mathematically is like learning to swim, to ride a bicycle, to ski, to play golf, or to play a musical instrument. You can probably get some idea by having someone explain it to you, but you won’t learn how to do it that way. The key words in that last clause are “learn” and “do”. There is really only one way to learn how to do something, and that is by doing it. Or, to put it more bluntly, the only way to achieve mastery is by repeated failure. You keep trying until you get it. The one thing that can help is having someone who already has mastery look at your attempts and give you constructive feedback.

In fact, failing in attempting to do something new isn’t really failure at all in the sense the word is usually used. Rather, a failed attempt is a step towards eventual success. Edison put it well when asked how he felt about his many failures to make a light bulb. He replied, “I have not failed. I’ve just found 10,000 ways that don’t work.”

After just one week of my course, I’ve seen a lot of learning going on, but it wasn’t in the lectures. Even if I’d been able to see each student watching the lecture, I would not have seen much learning going on, if any.  Rather, the learning I saw was on the discussion forums, primarily the ones focused on the assignments I gave out after each lecture. As I explained to the students, the course assignments and the associated forum discussions are the heart of the course.

So what is my part in all of this? Well, first of all, I have to admit I am uncomfortable with the title “instructor,” since that does not really reflect my role, but it’s the name society generally uses. “Course designer, conductor (as for an orchestra), and exemplar” would be a much better reflection of what I have been doing. Once the course was designed, the lectures recorded, and all the ancillary materials prepared, my task was to set the agenda, provide motivation and context for the various topics, and give examples of mathematical thinking.

The rest is up to the students. It has to be. (At least, I don’t know of any other way to learn how to think mathematically.) To be sure, in a physical class, the instructor (and or the TAs) can interact with the students, and (if it occurs) that can be a huge factor. But that simply helps the students learn by repeated failure, it does not eliminate the need for that learning-by-trying-and-failing process. Let’s face it, if you are not failing at something, you have already learned it, and should move on to the next step or topic. (With understanding, once you get it, you don’t need to practice!)

In a MOOC, that regular contact with the instructor and or the TAs is missing, of course. That means the students have to rely on one another for feedback. This is where the Coursera platform delivers. Here are some recent stats from my course website:

Total Registered Users 57592
Active Users Last Week 32123

Video Lectures

Total Streaming Views 77415
Total Downloads 19491
# Unique users watching videos 21712

Discussion Forums

Total Threads 641
Total Posts 5414
Total Comments 3823
Total Views 119489

Though I’d like to see a lot more students posting to the forums, with almost 120,000 views (after just one lecture and one course assignment!), it’s clear that that is where a lot of the action is.

As I surmised in an early blog-post, I don’t think it was the widespread availability of video technology and sites like YouTube that set the scene for MOOCs. To my mind, Facebook opened the floodgates, by making digitally-mediated social networking a mainstream human activity. (I’d better add Skype, since there are already several Skype-based study groups for my course. And of course, students who live close together can do it the old-fashioned way, by getting together in person to work through the assignments.)

One feature of the course that did not surprise me was the sense of feeling lost some students reported (and I’m sure many more felt), in some cases maybe being accompanied by panic. For most students, not only does my course present a side of mathematics they have never seen before (the world of the professional mathematicians), on top of that, none of the strategies they were taught to succeed in high-school math work any more.

Because the focus of the course is on mathematical thinking, I can’t provide the students with a list of rules to follow, templates to recognize, or procedures to follow. The whole point is to help them develop the ability to solve novel problems for which no  rules are known.

Of course, at this stage, the problems I give them are ones that have been solved long ago, and which have been shown to provide good learning material. But to the student, they are new, and that’s what matters in terms of learning. Unless, of course, they look for the solution on the Web, which defeats the whole purpose. But in a voluntary course where the focus is on process, not “getting answers,” and which provides no college credential, I hope that does not occur. In fact, one of the things that attracted me to free MOOCs was that the students would enroll because they wanted to learn, not because they were forced to learn or simply in need of a diploma. (We mathematicians get a lot of students like that! But we get paid to teach those classes. So far, no one is paying MOOC faculty for their efforts.)

Most US students have a particularly hard time with this “there are no templates” approach, because of the way mathematics is typically taught in American schools.  Instead of helping students to learn mathematics by figuring it out for themselves, teachers frequently begin by providing instruction and following it up with examples. Michael Pershan has a nice summary of this on YouTube. (His initial focus is on Khan Academy, but Khan is simply providing a service that is molded on, and fits into, the US system. The crucial issue Pershan’s video addresses is the system.)

The pros and cons of the two approaches, instruction based or guided discovery, remains a topic of debate in this country, but in the case of my course, there can be no debate. The goal is to develop the ability to encounter a novel problem and eventually be able to figure it out. Providing instruction in such a course would be like giving a golf cart to someone who wants to walk to lose weight! It might get them to their destination with less effort, but it would defeat the real goal.

Having thought at length about how to structure this first version of the course, and played around with some approaches, I ended up, as I thought I probably would, going minimal.  Virtually no instruction, and what little there is presented as examples of mathematical thinking in action, not by way of a carefully planned lesson. I was pretty sure I’d do that, because that’s how I’ve always conducted classes where the goal is student learning (as opposed to passing a standardized test).

There are a number of studies pointing out the dangers of over-planned lessons, one of the most famous and influential being Alan Schoenfeld’s 1988 paper in Educational Psychologist (Vol 23(2), 1988), When Good Teaching Leads to Bad Results: The Disasters of “Well Taught” Mathematics Courses. Still, as I said, I did play around with alternatives, since I was worried how students would fare without having regular access to the instructor and the TAs. I may have to re-visit those other approaches, if things go worse this time than I fear.

But this time round, what the student gets is as close a simulation as I can produce of sitting next to me as I work through the material. The result is not perfect. It’s not meant to be. There are minor errors in there. It’s meant to provide an example of how a professional mathematician sets about things. Definitely not intended as something to be perceived as an entry in an instruction manual.

After those work sessions were video-recorded, they were edited, of course, but only to cut out pauses while I thought, and to speed up the handwriting in places. I found that on a screen, watching the handwriting in real time looked painfully slow, and rapidly became irritating, particularly in places where I had to write out an entire sentence. So I took a leaf out of Vi Hart‘s wonderful repertoire. The speed ramping ended up being the only place that modern digital technology actually impinged on the lecture. Everywhere else it merely provided a medium. The approach would be familiar to Euclid if he were somehow to come back and take (or give) the class.

To be continued …

You may be interested in two recent videos featuring the founders of the two Stanford MOOC platforms that started the current explosion of interest in these courses. In one, Sebastian Thrun talks about Udacity. In the other Daphne Koller discusses the creation of Coursera.

The “C” in “MOOC”: MOOC planning – Part 6

A real-time chronicle of a seasoned professor embarking on his first massively open online course.

A few days ago, I went into our campus TV studio with the two course assistants for my upcoming MOOC, to record a short video introducing them to the students.  The students will see a lot of me, but my two TAs will be working behind the scenes, and the students will encounter them only through their contributions to the forum discussions. The videos were intended to compensate for that lack of human contact.

During the course of recording that video, the three of us got into a discussion about our backgrounds, our motives in giving the MOOC, and our views on mathematics, science, education, and our expectations for the MOOC format. The camera was rolling all the time, and we were able to select a few parts of that discussion and create a second video that I think will help our students understand some of our thinking in putting this course together.  I posted copies of both videos on YouTube.  (They are much lower resolution than the videos the registered students will see on the course website when it goes live on September 17 — the “first day of classes”.) I think the two videos provide an insight into our thinking as we designed this course.

The fact that the current round of MOOCs have a “first day of class” at all has been a matter of some debate. The C in MOOC stands for “course”, but is this the best way to go?  For example, see this blogpost from a graduate student at Berkeley, who argues for a more open framework of learning resources. He makes some good points that all of us involved in this initiative have thought about and discussed, but I’m not sure the kind of thing he advocates can work for disciplines and subjects that depend heavily on student-faculty and student-student interaction, as mine does.

In fact, I’m not sure the MOOC will work sufficiently well at all in such cases; this is very much an experiment that I anticipate will continue for several years before we get good answers either way. For the first iteration, it makes sense to start with a model we know does work. And important (we think!) elements of that model are, to repeat Sebastian Thrun’s list, as quoted in the Berkeley student’s blog: admissions, lectures, peer interaction, professor interaction, problem-solving, assignments, exams, deadlines, and certification. To use the mnemonic I coined earlier in this series, our basic design principle is WYSIWOSG: What You See Is What Our Students Get.

Since these courses are free, we can, of course, do a lot of A/B testing in future years, to see which of these truly are crucial, which can be changed and how, and which can be dropped. I suspect the answers we get will vary from discipline to discipline, and possibly from course to course.

All of us involved in this MOOC movement are trying to find out the best way that works for our particular discipline and is consistent with our own style as instructors. As I indicated in Part 4 of this diary, I think it makes sense to begin by trying to implement in a MOOC as much of our tried-and-trusted classroom-based teaching as we can (as Thrun did with Udacity), and then iterating in the light of what we learn.

This is why, instead of hiring a mathematics graduate student to TA my course, which is what I would have done for an on campus class, I brought onto my team two graduate students from Stanford’s School of Education with several years of experience in learning design and the use of technology in education. In addition to helping me with the design and running of the course, they will conduct research into the course’s efficacy and try to understand how learning occurs in a MOOC. (Other than a brief, non-compulsory questionnaire at the start and finish of the course, all their research will be based on data gathered on the Coursera course platform and human monitoring of the forum discussions. One huge benefit of MOOCs is that they facilitate Big Data research.)

It’s live beta, folks.

To be continued …

Khan Academy Meets Vi Hart: MOOC planning – Part 3

A real-time chronicle of a seasoned professor embarking on his first massively open online course.

The ideal way to learn mathematical thinking (and a great many other things that involve understanding, not just doing) is in a small physical group with an expert. That provides frequent opportunities to interact one-on-one with the expert, during which the expert can observe you work in real time (on paper or at a board) and can give you direct feedback on written work you have done and handed in for evaluation. It also provides frequent opportunities to discuss what is being learned with other students at the same stage of their learning, sometimes with the expert present, other times with the expert absent.

Sometimes, the expert will provide instruction. Though there have been successful instances of mathematics professors who largely avoid instruction (R L Moore being the most notable example), most of us (i.e., university mathematics educators) find that instruction has a valuable place in mathematics education. But many of us view it as just one part of mathematics education.

Anyone who has experienced highly interactive mathematics teaching will know how different it is from mere instruction, and how much more effective. I wrote about this last March in my Devlin’s Angle column for the MAA. Unfortunately, it seems clear that a great many Americans have never experienced good mathematics teaching. If they had, you would not have thousands of Khan Academy users (including famous figures such as Bill Gates) declaring Salman Khan is the best math teacher ever. You can say a number of good things about Sal Khan (I am going to say some of them in just a moment), but being a great math teacher is not one of them. To say that he is, simply reflects on the miserable math ed diet that many millions of American have been fed, for whom Khan Academy offers something far better than they were ever exposed to.

I bring up Khan Academy for a couple of reasons, one being that it set the stage for the MOOC explosion. Indeed, former Stanford CS professor Sebastian Thrun stated publicly last January that it was Khan Academy that inspired him to give his first MOOC in fall 2011, and then to leave Stanford and launch his own MOOC service Udacity at the start of this year.

It’s not merely the wide reach that Khan Academy demonstrated. As I discussed in a recent article for the MAA, Sal Khan managed to tap into the power of the Web medium to achieve a critical element of good teaching that not all teachers can offer: a strong teacher-student bond. Moreover, he did so using just his voice and the electronic trail of a digital pen on the viewer’s computer screen. Yes, some of the math is wrong, and the pedagogy is so poor, experienced teachers tear their hair out, but the very success of Khan Academy shows how important is the teacher-student connection.

Khan Academy is not a MOOC, of course, but it does provide a model for online mathematics instruction. In starting to plan my MOOC, I began by trying variants of Sal’s approach for the instructional part. Like him, I have a voice that works on the radio (or a Web audio channel) — an accident of birth — which makes such an approach feasible.

I soon concluded that his approach would not work. It is fine for presenting short instructional mini-lectures on how to follow a particular mathematical procedure, but it is woefully impoverished for trying to help students understand a mathematics idea or a proof, and to form the right mental concepts. For that, the huge importance in mathematics teaching of physical gestures, in particular the hand(s), cannot be ignored.

There is an old challenge in which you ask someone to describe a helix while keeping their hands clasped firmly behind their back. (Try it!) But it’s not just helices. Explaining almost any mathematical concept without using at the very least hand and arm gestures, and in many cases full body motion, is difficult if not impossible. There is masses written about this topic, based on many years of research. For example, take a look at this summary, or this one, or this forthcoming book. Or Google on the terms “mathematics + learning + hand + gesture” or variants thereof to see a lot more.

Since MOOC students access the material on a wide range of devices, with different screen sizes, I felt that a full body recording of me working at (and in front of) a blackboard or whiteboard would not be ideal. Besides, I love the sense of intimacy Khan Academy offers. You get a strong sense of sitting next to a friendly relative who is personally instructing you. I wanted to create that environment.

But trying to follow an explanation of a mathematical concept or proof Khan-style, where the visual channel consists only of a digital pen trace, was impossible — at least, it was given my educational style. At the very least, I needed my writing hand to direct the student’s focus. The simplest way to achieve that was to have a video camera mounted above my desk and record me working through the material in the time-honored fashion of paper-and-pencil. That seemed to work.

Having decided on the basic modality, the next issue was one of style and tone. After playing with some variants of the basic format, I came down in favor of a very informal look, where I simply slap down a sheet of paper on the desk in front of me and the student, and work through the material. (Marking the exact position of the paper on the desk and letting it totally fill the screen looked too artificial — though at this stage the issue was largely one of taste, and this is a decision I may change based on the experience I get from this first course. I did have to tape down the paper, but the initial placement was fairly casual, and the taping was sufficiently loose that the paper could still move a little — it takes effort to create “informality” on video.)

To counter the inevitable sense of frustration when watching a pen write something out in real time, I decided to speed up a lot of the writing during the video editing phase. (Though not to the speed of the wonderful Vi Hart, whose purpose is informative entertainment.) So at that stage I found myself with a “Sal Khan meets Vi Hart” look. A great place to start, given the success both have achieved!

For standalone Web instruction, that would likely be enough, but a MOOC involves a lot more. It is, after all, a course — a structured experience over several weeks, with a professor. Regular connection to the instructor is important — at least, I think it is. (It was for me when I was a student.) To achieve that “human connection,” many of my Stanford colleagues who have given MOOCs have put a small head-and-shoulders video of themselves speaking in one corner of the screen, as the material being discussed occupies the rest of the display. I tried that, and found it did not work for me, with my material. The face was a distraction. I wanted to keep as much of the Khan Academy sense as possible — you don’t ignore success unless there is good reason! So I opted to keep video of me separate from the hand-writing part.

I’ve posted a short sample from Lecture 1 on YouTube. Given the low resolution of YouTube video encoding, this does not display well in terms of content, but the Coursera platform uses far higher resolution video.

I doubt much of this material will survive to a second iteration of the course next year. At the very least, I’d want to go back and pay more attention to lighting and audio levels and consistency.  But it does have the overall look and feel I was trying to achieve. This is live beta, folks.

But as I have already indicated in this blog series, I don’t see the video lectures as the heart of the course. They merely set the agenda for learning. The real learning takes place elsewhere. I’ll turn to that topic in a future post.

Meanwhile, my Stanford MOOC Introduction to Mathematical Thinking is scheduled to begin on September 17 on Coursera. If you want to do some preliminary reading, there is my low-cost course textbook by the same name. Though written to align to the course, it is not required in order to complete the course. (Indeed, I noted  above that I see MOOCs as replacing textbooks — though some MOOCs may have required textbooks, so it would be unwise to predict the imminent death of the printed textbook!)

To be continued …

NOTE: I mentioned Khan Academy to indicate its role in the MOOC explosion and acknowledge its role in guiding the design of the instructional videos in my MOOC. But the focus of this blog is on MOOCs in general and mathematics MOOCs in particular. Comments discussing the merits or demerits of Khan Academy are off topic and hence will not be published; there are many other venues for such discussions.

Let’s teach the world

This coming October, I’ll be offering my first MOOC — massive(ly) open online course — one of a growing number of such offerings that have started to emerge from some leading US universities over the past few months. In this blog, I’ll chronicle my experience as it happens, and hopefully get useful feedback from others. This introductory post is a shortened version of my May 1 blogpost on Devlin’s Angle for the MAA.

Higher education as we know it just ended. Exactly what will take its place is not at all clear. All that can be said with certainty is that within a few short years the higher education landscape will look very different.

That is not to say that existing colleges and universities will suddenly go away, or indeed change what they do – though I think both will occur to varying degrees in due course. What is changing now is what classifies as higher education, who provides it, how they provide it, who will have access to it, how they will obtain it, and how it will be funded. Distance education, for many years the largely-ignored stepchild of the higher education system, is about to come of age.

This is not just my opinion. My own university, Stanford, recognizes what is going on, and is taking significant steps to lead and stay on top of the change, and a number of Silicon Valley’s famed venture capital firms, who make their fortunes by betting right on the future, have sunk significant funding into what they think may be key players in the new, higher ed world.

Last fall, Stanford computer science professor Sebastian Thrun used the Internet to open his on campus course in artificial intelligence to anyone in the world with Net access, and 160,000 students from 190 countries signed up. Some 22,000 of those students finished the course, receiving “certificates of completion” signed by Thrun (and co-teacher Peter Norvig of Google), but no Stanford credit. (For that, a student has to be on campus and officially registered; annual tuition is $40,050 and entry is fiercely competitive.)

Demonstrating the entrepreneurial spirit that Stanford faculty are famous for, Thrun promptly left Stanford to found a for-profit online university, Udacity. With Udacity receiving financial backing from a large Venture Capital firm, the MOOC – massive open online course – suddenly came of age. A short while later, two more Stanford computer science faculty, Andrew Ng and Daphne Koller, secured $16M of venture capital funding to launch a second Stanford spin-off company, Coursera, a Web platform to distribute a broad array of interactive courses in the humanities, social sciences, physical sciences, and engineering.

Initial courses offered on Coursera include, in addition to several from Stanford, offerings from faculty at the University of Michigan, the University of Pennsylvania, and Princeton. Stanford president John Hennessy appointed a blue-ribbon panel of Stanford faculty to develop a strategy for developing, and delivering, online courses. For free. To the world.

Not wanting to be left behind, just this week, MIT and Harvard announced the launch of edX, a joint effort to mount their own MOOC distribution platform, with each institution committing $30M to the project.

Yes, you read that correctly. The faculty, the universities, and the new platforms are making the courses available for free. All the funding is coming – for now – from for-profit investors and the private universities themselves. Why are they doing that? If you have to ask the question, you don’t really understand the Internet and how it changes everything. Think Napster and the music industry or Skype and the telephone industry. Like the settling of the American territories in the nineteenth century, the initial focus is on establishing a presence in the new land; monetization can come later – almost certainly in ways very different from today’s.

Computer-assisted, distance learning is not new, of course. Stanford was one of the universities that pioneered it the 1960s; many universities have for several decades offered adult professional education courses for a fee, largely to raise funds; and there are the for-profit online schools like the University of Phoenix. More recently, led by MIT, a number of universities started making recordings of their regular courses, together with course materials, available online for free. So what has changed now?

The answer is the platform and the target audience’s experience and expectations have changed. What has been missing so far is the active participation of the distant student in a learning community. Building on technology developed at Stanford to support flipped classroom experiences for its regular students, Udacity and Coursera have secured the major investments required to build scalable, robust platforms that can take the small learning seminar and create a similar experience across the Internet.

A generation that has grown up on the Web has taken to the new online learning medium like fish to water. For instance, during the term when Thrun made his AI course available online, most of the Stanford students enrolled in his class stopped attending his lectures and took their information delivery online, at times convenient to them. But the convenience of Stanford students is not what the MOOC initiative is about. What excites me and my colleagues is the possibility to reach millions who currently have no access to any university at all.

Welcome to the age of the MOOC.



I'm Dr. Keith Devlin, a mathematician at Stanford University. In fall 2012, I gave my first free, open, online math course. I repeated it in spring 2013, then in fall 2013, and in February I am giving it a fourth time, each time with changes. This blog chronicles my experiences as they happen.

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