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In “Dancing with the Stars” I talked about what a classroom with 10,000 students might be like. The transformation of higher education has begun, and the pace of that change is accelerating.

Dick Lipton’s blog Godel’s Lost Letter has since attracted tens of thousands more.  It is a virtual seminar that, for example, coordinated a global effort to referee an important paper in the theory of algorithms.  At times, the number of viewers topped 100,000. Now Stanford’s Peter Norvig and Sebastian Thrun are offering an online course in artificial intelligence that will enroll 58,000 students.

On September 12, I will join with 60 or so colleagues to offer a MOOC for tens of thousands of students.  Georgia Tech  students will get credit, and others will get badges that could be convertible to credit if they ever enroll at Tech.  Other institutions will announce their approaches to certifying achievement in the course. A MOOC is a Massive Open Online Course, a style of college-level teaching that was pioneered by George Siemens and Stephen Downes. The first MOOC, offered in 2008 by George and Stephen was devoted to the subject of their research, a style of learning called connected connectivism. It attracted 10,000 students.

The 2011-12 MOOC is all about transforming university learning and the organizers hope it will attract a much wider global audience.  They are calling it the Mother of all MOOCS.

The course will also be a C21U experiment on self-certification, a concept I discussed in my book. Where will this all lead?  It’s far too soon to predict an outcome, but within the last year, the number of experiments in higher education has exploded.  If you believe like me that innovative change is just what traditional colleges and universities need, that’s a good thing. The way to innovate is to try out lots of ideas.

Crazy claims about faculty productivity are bouncing around like ping pong balls.  Public research universities in Texas are getting more than their fair share of attention from agenda-driven politicians because their professors are not spending enough time in class.  They’ve even invented a classification system based on this one-dimensional view of academic life:

  • dodgers
  • coasters
  • Sherpa
  • pioneers
  • stars

I don’t think I’d want to be a coaster, but to be honest, I wouldn’t want to be a Sherpa, either.

CCAP’s Richard Vedder has looked at the same data through a conservative economic lens and concluded that significant costs savings can be found by adjusting teaching loads — upwards, of course. Like CCAP I think there needs to be more emphasis on undergraduates, but just lopping off a part of an institutional mission is not the way to do it.  Unless, of course, you are of the opinion that everything outside the classroom is overrated in American universities.

Maybe I travel in different circles, but the faculty workday appears to me to be an already overstuffed suitcase.  Anyone who wants to cram in another sock needs to take a look at what’s already there. Mission creep, bureaucratic bloat, crushing compliance requirements, and the willful bliss with which research universities give away research time have filled every nook and cranny.

I talked a few weeks ago about how research is given away, and it’s a topic that always draws phone calls and email.  But let’s take a look at the same data that CCAP uses.  The John William Pope Center recently published a national analysis of teaching loads.  It should come as no surprise that they have gone down over the last twenty years, but more interesting is the trend.

The decreases virtually track the increased workload by program officers at Federal funding agencies. But since staff spending at agencies like NSF has been stagnant for twenty years, program officer workloads really just measure proposal submissions.

Why the decrease at Carnegie Research and Doctoral institutions?  According to an NSF study the tendency in most NSF program offices is to deliberately underfund project proposals.  Over half of the researchers surveyed reported that their budgets had been cut by 5% or more and that their grant duration had been slashed by 10% or more.  There is little room for padding an NSF budget, so these are real cuts in funds that are needed to successfully complete a research plan. One more sock stuffed into the productivity suitcase.

What does a winning proposal cost?  The same study reported:

…PIs’ estimate of the time it took for them and other people—for example,
graduate assistants, budget administrators, and secretaries (not including time spent by
institutional personnel)—to prepare their FY 2001 NSF grant submission was, on average, 157
hours, or about 19.5 days. It should be noted this is the time for just one proposal that was
successful.

Since the NSF success rate is currently around 25%, that’s about 80 days just to prepare a winning proposal.  Add to that the time needed to conduct the research that goes into every proposal submission, and you get a rough idea of what needs to be funded just to make research pay for itself.  This is lost productivity, and it shows up in reduced faculty teaching loads.

The trends at Comprehensive, Liberal Arts, and Community Colleges measure something slightly different: each of these institutions sees climbing the Carnegie hierarchy as important to their missions.  For example, NSF awarded $350M to community colleges last year.  The lions’ share of these funds went to worthy projects to train technicians, broaden participation in the sciences and support research experiences for returning veterans.  Individual awards for some of these programs start at $200,000 and solicitations for larger, center-scale proposals are encouraged. Like their research cousins, Community Colleges reduce classroom productivity to compete for federal research awards. An institution with an undergraduate research mission can easily get drawn into a system they cannot afford. And the data supports the claim.  For the period covered by the Pope Center report, proposal submissions from these institutions have increased almost in lockstep with lost classroom productivity.

Measuring technical productivity is not a job for the faint of heart. You have to take into account all uses of time, and outcomes that are often unpredictable events influenced by factors beyond an organization’s control. Modeling productivity is complex and frequently contentious, but I have yet to find anyone who seriously proposes measuring engineering productivity by the amount of time spent at a single activity.  Outside higher ed.

There is an easier explanation for the disturbing downward trend in teaching loads. It is mission creep.  There is really only one way out, and it has nothing to do with cramming more into a Texas-sized suitcase.  How about if everything from sponsored research to intercollegiate athletics had to pay its own way?  The academic suitcase is full of stuff already.  Let’s figure out where to put everything else one sock at a time.


I’ve been spending more time with alumni.  Zvi Galil, the new dean of computing at Georgia Tech — my successor — has been on a national tour to get acquainted with recent graduates. I accompany him whenever I can to make introductions and to generally help smooth his transition.  Not that he needs it.  Zvi was dean of engineering at Columbia for many years and knows how to get alumni to talk honestly about their undergraduate experiences. We were having lunch with a group of recent graduates when I heard Zvi ask someone at the end of the table, “What’s the one thing you wish we had taught you?”

The answer came back immediately: “I wish I had learned how to make an effective PowerPoint™ presentation!”  If the answer had been “more math” or “better writing skills” I would have filed it away in my mental catalog of ways to tweak our degree programs. It’s a constant struggle in a requirement-laden technical curriculum — even one as flexible as our Threads program — to get enough liberal arts, basic science, and business credits into a four year program, so I was prepared to hear that these young engineers wanted to know more about American history, geology, or accounting. After all, I am a former dean.  I had heard it all before.

But PowerPoint? Everything came to a stop.  Zvi said, “PowerPoint!” It was an exclamation, not a question.  Here’s how the rest  of the conversation unfolded” “Look, the first thing I had to do was start making budget presentations. I had no idea how to make a winning argument.”  From the across the table: ” Yeah, we learned how to make technical presentations, but nobody warned us that we’d have to make our point to a boss who didn’t care about the technology.”  “It’s even worse where I work,” said a young woman. “Everybody in the room has a great technology to push.  I needed to know how to say why mine should be the winner.”  And so it went.  This was not a PowerPoint discussion.  We were talking about Big Animal Pictures. If you understand Big Animal Pictures, you understand  how to survive when worlds collide.

David Stockman directed Ronald Reagan’s Office of Management and Budget (OMB) from 1981 to 1985.  He was a technician.  A financial engineer. He had a Harvard MBA, and spent the early part of his career on Wall Street with Solomon Brothers and Blackstone. It was a checkered career, and if you take seriously the accounts in his memoir of the Reagan years, he never really understood that he was caught between colliding worlds. Which brings me to Big Animal Pictures.

Stockman was a conservative deficit hawk who thought his job was to restore fiscal sanity.  Reagan had beaten Jimmy Carter in part by painting the Democrats as financially irresponsible.  David Stockman’s job was to fix that, and that meant budget-cutting.  Defense Secretary Caspar Weinberger thought that Reagan had been elected to restore America’s military might. Weinberger’s job was to pump more money into defense budgets.  Stockman and Weinberger were on a collision course, and for a year they traded line-item edits to the federal budget. This was a technical duel. Stockman and Weinberger both had considerable quantitative skills. It was a bureaucratic game that Weinberger had learned to play when he worked for Reagan in California, but there was a deepening recession. In the end, it appeared that DoD would have to make do with the 5% increase that the White House was proposing. It was a spending increase that Stockman believed was unwise and unaffordable.

Weinberger’s proposal was 10%.  Stockman could barely contain himself. It set up a famous duel in the form of a budget briefing with Reagan playing the role of mediator. It was going to be a titanic debate.

Stockman showed up with charts, graphs and projections.  The stuff that the OMB Director is supposed to have at his fingertips. Weinberger came armed with a cartoon, and walked away with his budget request more or less intact.

Weinberger’s presentation was a drawing of three soldiers. On the left was a small, unarmed, cowering soldier — a victim of years of Democratic starvation. The  bespectacled soldier in the middle — who bore a striking resemblance to Stockman — was a little bigger, but carried only a tiny rifle. This was the army that David Stockman wanted to send to battle. The third solder was a  menacing fighting machine, complete with flak jacket and an M-90 machine gun. It was the soldier that Weinberger wanted to fund with his defense budget.  Weinberger won the budget debate with Big Animal Pictures.

Stockman was appalled:

It was so intellectually disreputable, so demeaning, that I could hardly bring myself to believe that a Harvard educated cabinet officer could have brought this to the President of the United States. Did he think the White House was on Sesame Street?

Stockman and many analysts concluded that the episode revealed something deep about Reagan’s intellectual capacity. Maybe so, but I think it revealed more about Weinberger’s insight into what it takes to carry an argument when the opposing sides can each make a strong technical case for the correctness of their position: argue for the importance of the end result, not for the correctness of how you will achieve it. It is a classical colliding worlds strategy.

Michael Dell’s 1987 private placement memorandum for Dell Computer Corporation was a Big Animal Picture. Buying computers was a hassle when Dell started his dormitory-based business in 1984.  By 1987, PC’s Limited had sold $160M worth of computers based on a simple strategy: eliminate the middle man, get rid of inventories, and give customers a hassle-free way to buy inexpensive, powerful IBM-compatible computers.  In the midst of a stock market crash, Michael Dell managed to raise $21M based on a short document that ignored the conventional view that private placement business plans had to be highly technical:

Dell has sold over $160 million of computers and related equipment on an initial investment of $1,000. The Company has been profitable in each quarter of its existence, and sales have increased in each quarter since the Company’s inception.

Tacked onto the memorandum, almost as an afterthought were letters from customers — inquiries from people who were interested in buying computers from Michael Dell and testimonial from owners of his made-to-order PCs who wanted to buy more of them.  It was short (45 pages with the letters attached) and, aside from a few pro-forma financials to explain what would be done with the new money, it was almost entirely devoted to painting a picture of what success looked like to Michael Dell.

A copy of the original Dell memorandum wound up on my desk in late 1998.  At the time, my Bellcore department heads were struggling to define businesses that could either be spun out of the company or funded as internal startups. I was drowning in  highly technical market forecasts and details of patent disclosures. Each new spreadsheet screamed: “Idiot! Just look at this equation.  It’s obvious why our approach is better than everyone else’s.”  One afternoon, in exasperation,  I threw Michael Dell’s private placement memorandum on my conference table and said “Make me a presentation that looks like this.” The room got very quiet as they realized what was going on.  I was asking for Big Animal Pictures.

We started four businesses within 18 months.  Three were spun out  and made a modest amount of money for the company and the founders.  We ran one as an internal start-up. It did not do nearly so well. One of the key factors was that we could not duplicate Michael Dell’s Big Animal Picture.

This is not a lesson that engineers and scientists learn easily. In fact, when presented with overwhelming evidence that business decisions are seldom made on the basis of technical elegance and correctness, engineers retreat to the safer ground staked out by David Stockman: “Do you think we are on Sesame Street?” The answer is “Yes!”  Successful engineers and scientists know all about Big Animal Pictures.

Paul R.  Halmos was one of the great mathematicians of the 20th century. He studied the most abstract topics imaginable. One of his crowning achievements, for example, was to create an entire algebraic theory to describe mathematical logic, which was itself an abstract mathematical theory to explain symbolic logic. Symbolic logic was, in turn, an abstract explanation of the kind logic used by Aristotle, and Aristotle’s logic was the formalization of correct patterns of human  inference. Halmos did not deal in uncomplicated matters.

How did Paul Halmos counsel young mathematicians to present their work in public?

A public lecture should be simple and elementary; it should not be complicated and technical. If you believe you can act on this injunction (“Be Simple”) you can stop reading here, the rest of what I have to say is, in comparison, just a matter of minor detail.

The mistake, Paul Halmos noted in his essay How to talk Mathematics is thinking that a simple lecture talks down to the audience. It does not. Halmos (or PRH as he sometimes called himself) seems to have understood worlds in collision.   Of course, a simple lecture in PRH world might open with the phrase “…as far at Betti numbers go, it is just like what happens when you multiply polynomials,” so it’s a sliding scale.

No matter what you’re doing in the technical world, learning how Big Animal Pictures work is a valuable thing.  I sometimes sit on review panels to decide on research funding.  I recently advised a young scientist to use Big Animal Pictures.  She had five minutes to present her work and I knew that the competition would be strong.  Her first instinct was to jump into the technical meat of her research to give the reviewers a feeling for why her approach was better than other approaches. My advice was to not do that.  I wanted her to literally give a BAP presentation that would inform the panel about the importance of her research and why they should care about it.  I later found out that other colleagues had given her identical advice, which she apparently followed with great success.

And it doesn’t matter which of the colliding worlds you are on.  BAPs are always a good idea. My colleague Wenke Lee was recently called upon to give a presentation on the state of computer security research to a  group of mathematicians.  It was all about how powerful mathematics can be used to exploit security flaws and vulnerabilities. Wenke resisted the temptation to dive into the technical details of botnet attacks.  It is, after all, a subject he knows well and he probably would have had fun demonstrating his prowess. But here is how Wenke began his lecture.

He went on for another twenty minutes, but he really didn’t need to. Everyone got the point in the first thirty seconds.

Even casual iTunes™ users know about iTunesU™, the increasingly rich video-taped course offerings from universities as great as Stanford and Oxford and as humble as the dozens of community colleges and adult education programs that make their curricula available for free downloading. I should have seen it coming in the spring of 2001 when Charles Vest – then president of MIT – paid me a visit at HP to tell me of his plans to make MIT’s entire course catalog available for download on the internet, but I was not thinking much about Higher Education as a market in those days.

Things changed in late 2002 when I started to draw a paycheck from a university and began to think hard about the fate of American colleges and universities in the 21st century.  What Chuck Vest predicted one afternoon in my Palo Alto office is now being played out in what I believe is the next economic bubble.  This is quite literally the collision of that half of the earth’s population that has in the last decade joined the free market economy with the inwardly focused world of  Americah higher education, which – unless there are some dramatic changes – is destined to be a marginalized bystander to events that it is ill-equipped to understand.  Here is the stark reality: enhanced technology means that the market for higher education now has many suppliers, and the  hundreds of millions of people who all of a sudden want a university education also find that they have abundant choices, often with lower cost and high quality.    In any market with abundant choices, the winners are inevitably those with compelling brands, price, or value.  There are about 3,500 accredited colleges and universities in the US, and, except for the handful (less than a hundred) who have global brands, most of them have not figured out how to deliver their value at an acceptable price.  In fact, an alarming large number of them cannot even articulate their value to the world that is rushing toward them.  That spells trouble. I will have much more to say about WWC and higher education in later posts.

I am working on a book on this topic so these problems are much on my mind these days, but an email message from a colleague prompted me write that there may be a series of smaller collisions rather than a single cataclysm.

There is a lot of criticism about the quality of iTunesU lectures and online courses.  Some criticism can be dismissed as an “innovator’s dilemma” confusion of the current state  — much of it admittedly primitive – of the technology with its disruptive power.  I find this criticism easy to dismiss because you can see quality of online instruction improving month by month.  Never underestimate the power of technology curves.  The more difficult question is how exactly the technology can replace a skilled human mentor who has ability to interact directly with her students.

Then two e-mails from my friend Dick Lipton showed up.  “Hit 7,000 page views today!” said the first one.  A few hours later: “We were number 20 on WordPress!”  That’s 20 out of roughly 3 million WordPress posts.  Dick is a world-class computational theorist, a member of the National Academy of Engineering and one of the best teachers I have ever known.  He is a star.  He has been blogging pure math for the last year at a website called “G̈ödel’s Lost Letter¨.  Not exactly the stuff you would expect to be in the top  .0007% of all of those posts about Michael Jackson, Death Panels, and the 2016 Olympics.  His latest series “Reasons for Believing P = NP” has been exceptionally popular, drawing hundreds of comments from experts, novices, interested amateurs, and a few cranks.  We have been collaborators for many years. Our offices used to share a common wall.  I know Dick’s voice when he is engaged with his students.  It has a distinctive rhythm and is louder when he is trying to extract a missing argument from a reluctant pupil.  It was the voice I heard when I read his blog, and as I thought about his 7,000 viewers it occurred to me that Dick’s seminar was no longer 10 or 15 graduate students crowded around a white board.  This is not an on-line lecture or an iTunes™ videos. I thought, “This is what the teacher-mentor relationship is like when the technology enables a classroom of 7,000 students.”  When there are abundant choices, students will choose this.