Speed to expertise in five easy steps

By now we all have heard of Malcolm Gladwell's "10,000 hour rule," which he put forward in his book Outliers. If you want to master something, you need something like ten thousand hours of serious, dedicated practice. Only then can you become truly outstanding. This isn't original with Gladwell, three guys named Ericsson, Krampe, and Tesch-Romer were writing about this in 1993 (look here). It's a very persuasive argument, but it doesn't help much when you're trying to teach students or train employees. "Okay, I think you've got the hang of it now. Keep practicing that, and I'll be back in about... oh, ten years or so to see how you're coming along."

The fact is, we need an acceptable level of mastery, and we need it now. We don't need to split the arrow; we need to hit the target. We need competence. So the question becomes, how do we get this level of mastery out of a novice within the normal time frames of actual life. Or if not life, then education--classes, courses, semesters, and programs. Is it possible? How is it possible?

Here are five answers which, interestingly enough, come from the field of... expertise. Yes, there are people whose expertise is expertise. David F. Feldon is one of them, and he has an oft-quoted paper to prove it... all about the role of expertise in pedagogy and curriculum. Download it here, It's worth a read. But then, if you were looking for a scholarly article you probably wouldn't be storming the blogosphere, so let me pick a little low-hanging fruit and serve it up with the chilled wine of my own experience and observation. (I'll try to keep the cheese to a minimum.)

One. It's not just knowledge. The popular idea that experts simply know more is untrue. Wait, they do know more... that part is true. It's the "simply" part that is untrue. What experts do with their knowledge, how they manipulate it, how they categorize it, how they think about it, or don't think about it... that's what makes them experts.

Practical application: Knowledge is only one factor, so don't focus on it exclusively. "Death by PowerPoint" leads not to expertise, but rather to death. Or at least a semi-comatose state. You really need to start with how experts got to be experts in the first place.

Two. Don't count on experts to tell you how they got to be experts. The accuracy of self-reports by experts has been studied, and the results are not encouraging. Just to pull one of Feldon's little nuggets from its context: "...self-report errors and omissions increased as skills improved." (p.99) What this means is, many experts don't know, and may even misrepresent, how they got so good. My own experience is that world-class experts, and I've dealt with a few, are often wrapped snugly in the soft, warm blankets of ego, and will always have an answer for you, even if it's wrong. Or even if it comes not from sober reflection but rather from that mini-myth that is the human self-image. Which in experts has sometimes grown greater, and more mythical, in concert with the accolades.

An example... the big league pitcher who explained that the secret to his curve ball was the way he spun his fingers as he let go of the ball. Until slow-motion cameras clearly showed that the ball had already left his hand and traveled a foot or two before those fingers did their twitching.

Practical application: Let Superman save you, but trust Lex Luthor's data. (Hey. He's a scientist.) Use and choose content based on the data--what the experts in your field actually do, and don't do, as measured by people whose job it is to measure it.

Three. Big Buckets. Experts know how to sort through new data, new situations, contradictory information, just about anything that falls within their area of expertise, and place it into an appropriate category in order to address it, resolve it, or perhaps ignore it. You've seen this a thousand times, whenever you're dealing with an expert in an area in which you are not one. Take me and my auto mechanic. "The car kind of vibrates and makes a funny noise," I say. "Does the steering wheel vibrate?" He asks. "The whole car!" I answer. But what he's doing is going through systems. He's categorizing, eliminating possibilities. If the steering isn't particularly affected, it's probably not front end alignment. So then he probes some other category. "Is the noise always the same?" "Well," I answer, "it's a lot less noticeable when I turn the radio up." (I did say I wasn't an expert.)

Practical application: Teach categories right from the start. The categories are something you actually can get with accuracy from those same vaunted experts... and you want the categories that the experts use, not the ones that the textbook writers use. It may take a little probing, but your SME will give you his or her big buckets. And those buckets are what learners need, so they have a practical place to keep and carry all the knowledge from those PowerPoint slide decks.

Four. Principles and theories. Experts know their way around the theoretical framework of their field, and are not typically hindered by what the answer "should be." A novice will assume a required solution and try to get there any way possible, usually by trial and error, while an expert will back up, assess all the inputs in light of their whole frame of reference, which is bounded only by the principles that underlie all solutions. Then the expert will get to the answer on a much deeper, more permanent level.

Here's an example. Remember the "I Love Lucy" scene where the candy conveyor belt was moving too fast for Lucy and Ethel? Me neither, not that old, but I found it online here. This is classic comedy, but it's also classic (though exaggerated) novice behavior. "Stop the candy from going by too fast" is their assumed solution, what they're trying to accomplish, but their frame of reference is limited to what they know how to do (grab candy, wrap candy, eat candy), and so everything they try is a bigger, funnier failure. But an expert would understand the bigger picture, the more general concepts, and so would know how the conveyor belt works, where to find a kill switch, when to go get help to avoid a bigger crisis. Shut it down until you get it right, would be the expert's general principle.

Practical application: Teach the big, underlying principles. Maybe you're doing training, and you're thinking this is no place for graduate level content. But knowing only the nuts and bolts is not going to lead to expertise, or even to competence, but to chaos.

But then... the principles alone won't do it either. You need...

Five. Automaticity. Automatic-ness. The ability to perform the simple parts of complex functions subconsciously. Automatically. Experts don't have to think through everything, they can think about the higher-level requirements because the lower-level requirements are on auto-pilot. From Feldon (p. 98):

Expert sight-reading performance in music is a clear example of this process. While playing music with typical features, expert pianists rely on automated skills to recognize patterns and strike the appropriate keys in sequence (Lehmann & McArthur, 2002). Concurrently, they dedicate their conscious processing to dynamic synchronization with other performers. When the novelty or visual complexity of the sheet music exceeds the threshold of transfer for automated sight-reading skills, the musician engages in effortful, deliberate encoding to mediate the execution of the necessary subprocesses.

Translation: Sight-reading the music has to be automatic so they can focus on the art. When it's not automatic, they have go back and practice to make it automatic.

Practical application: Drill and practice, baby, drill and practice! Maybe it's out of fashion, but the fact is, "acquired automaticity facilitates the development of expertise." Maybe your learners need to know how to answer certain customer questions, or deal with certain patient behaviors, or use a handful of complex formulas over and over to get to complex solutions. Get the new recruits to memorize. Drill them until they can do the core parts of it every time, even if that means giving them six or eight or fifteen statements that should be said to customers, all the time. "Mantras," if you will. Work with learners on those few, key, foundational skills or knowledge sets until they are automatic with them, this will absolutely increase their speed to expertise.

To sum up, you can get to competence a lot quicker than 10,000 hours if you follow the path that experts take. Teach them the knowledge, but always within the big buckets that experts use to solve problems. Give them the principles and theories, the framework on which the required behaviors stand or fall. Drill them on the key behaviors that should be automatic.

And never let the experts convince you they know how they got to be experts. Unless of course, your experts are experts on being experts.

Swarm theory to learning theory

I don't see a lot of people drawing connections between swarm intelligence and learning theory, and I don't know why. The two are inextricably linked. Swarm intelligence, for those of you who are not bio-researchers, sci-fi fans, or robotics aficionados, is that area of science where smart people in lab coats try to figure out how incredibly stupid beasts like ants and termites can build complex cities with skyscrapers that would actually put ours to shame if the scales were equal. Check out this link about the African termite. Air ducts, temperature regulation, recycling, they have it all.

The Artificial Intelligence (AI) community loves this stuff, because it gives them hope that they can actually build a smart robot. They have had enormous trouble trying to go at creating an artificial brain as sophisticated as ours by programming it in the classic model. "Let's see, now, this line of code says that if I'm standing in wet grass in sandals on a cold day holding a grocery bag and need to carry it up a slope, and if the slope is x1, y1.2 or greater and the moisture level exceeds..." You can see how they might run into trouble after a few hundred million lines of code. It starts to get buggy pretty quickly.

So what they've done, in an almost perfect pivot for anyone who appreciates a good (or bad) pun, is they've quit worrying about bugs and started studying them. They've quit thinking about people brains and started thinking about bug brains. They've discovered that the little critters only have so much code in their heads, very simple commands like, "if another ant has been here before, drop a pellet on this spot." Simple code, and not much of it. But when you put 20,000 of these tiny, illiterate insects together randomly, and turn them loose to follow those simple commands, they actually behave as though they were intelligent. As though there were some master plan or brilliant top-down management. The whole is truly far greater than the sum of the parts. (Which is one reason this is also called "emergent intelligence," the idea being that smart behaviors emerge from non-smart creatures under the right circumstances).

You can see how an AI guy might really like this angle of pursuit. Not a billion lines of code, but a few hundred thousand. And guess what, it works. Their study has already yielded practical results, on the market today. By creating software-based pseudo-termites, little programs that only know how to do a few things, and filling up a software program with these agents, they can start to imitate, essentially to create, this kind of intelligence. Southwest Airlines uses what is called ant-based routing programs to help pilots find gates most effectively. The movie industry creates all its huge battle scenes this way now, in software programs, by giving all the animated characters the same set of rules (like, "Try to take the enemy's head off with your sword," and, "If you lose your sword, stab them with your knife."). This technology was pioneered in a program called Massive, used first in the Lord of the Rings trilogy. And that turned out pretty well.

But AI scientists want more, of course, they want a human brain. And they have made some cognitive connections that are stunning. Like, for example, they will tell you that the entire human brain works just like an ant-based routing system. The neurons are the little bots, and the synapses are how they communicate with one another, essentially how they are thrown together randomly and run around together. These programmers now figure that if they can get the right "little bot" coding, they can recreate a human brain. The old saw that a software program can only do what you program it to do just doesn't hold anymore. Going about it this way, it might do anything (Anyone remember HAL? or I, Robot?).

Okay, so what has all that got to do with learning theory? Well, everything, considering that what the little bots end up with is more, and different than, what they started with. The entire process of what we call intelligent behavior could well be called learning. There may not be a difference. But aside from everything, the answer is: let's focus on small, simple codes and instructions. Did you read Good to Great, by Jim Collins? (If not please do... I'll wait. It's worth it.) Jim's research came to the conclusion that great companies, not just good ones, but truly great companies have a singular focus on a few, easily understood, highly motivational principles. He calls them together the "Hedgehog Principle" for reasons you will understand if you read the book. What he's saying is, that people who focus on a few simple rules, commands if you will, and get a whole lot of semi-intelligent agents (ie, employees) out there doing everything they can to make those simple things true, you will have something truly outstanding emerge. Like maybe, the equivalent of a 160-story skyscraper. Or Southwest Airlines. This is empowerment to the Nth degree. So long as the employees are pursuing these simple goals, and they're the right goals, they will create something unstoppable.

Now, from learning to training: Train the goals. We spend a lot of time as educators, trainers, e-learning professionals, focusing on cognitive theory, learning preferences, gap analyses, performance assessment... but what if, without abandoning all that, we just lowered the intensity a bit? And what if we raised the intensity of identifying those four or five key things that, if everyone knew and followed them, and then applied them to their own circumstances, would result in something bigger than the sum of the parts? What if we let go of a little control, focused more on measuring that our learners understood and bought into the main mission, and that they could (and that they wanted to) apply it to whatever they did, and we focused a little less on analytically measuring whether they can lock the widget onto the wonket? They'll figure out widgets and wonkets, if they know the end game, and are committed.

Swarm theory. It's a learning theory waiting to be applied.

Feedback about feedback

Most of us who've been doing eLearning for any length of time know all about Kirkpatrick's Four Levels of assessment, and we work hard to get as high up that ladder as possible. What are learners learning, and how is it affecting their world? But how many of us know about the Four Levels of Feedback?

We know how important it is to provide learners with constructive inputs along the way, and to adjust instruction to match needs. That's formative assessment--basic learning strategy, right? If you're like me, though, feedback is mostly a check-mark. Is it built in somewhere, or is it not? If you've got it, that's good--and it will be good for the learner. The research base is well established. And if you're like me, you also know that providing more specific feedback ("The correct answer is X because...") is much better than providing less specific feedback ("Wrong!"). Make the feedback as positive and as ubiquitous as you reasonably can, provide some guidance for improvement, and drive on.

But then recently I stumbled on John Hattie and Helen Timperley, and the four "levels" of feedback they delineate in their article The Power of Feedback (Review of Educational Research, March 2007). Their work sums up a lot of other research, but makes it, I think, much more approachable--providing a practical "handle" for actually using it. It seems to me they've done for feedback what Donald Kirkpatrick did for training assessment. Let's take a look.

The Four Levels of Feedback:

1. Feedback about the task. This is the one that I, at least, tend to think of as "feedback" unless someone focuses me on something more or different. "That is correct, sir," or "You got it right!" or "You missed this, try that." It's corrective. The learner has to achieve something, and you want to let them know whether they achieved it or not, and help them improve. Turns out that while this is helpful, it's not the most helpful feedback you can offer.

Level One feedback can be, and usually is, built into eLearning in some fashion. It's often automated.

2. Feedback about the process. The "correction" in this case focuses not on the outcome, or the work product, but the way the outcome is being developed. "You've got an interesting result here, but did you come to it by the means we discussed in class?" Which may be another way of saying, you didn't get the answer right because you didn't go through the appropriate steps. But that subtle difference is important. The writing process, the design process, even the scientific method... you focus the learners on the process they're using, on whether or not they are taking the right steps, and you leave the result (the work product) more in their hands. You can see how it would energize a learner, provide motivation to go on improving his or her work product, when you give them room to fix it themselves by going back to their approach.

Level Two feedback can be done online, but it's tough to automate it, unless the process being taught is also online. Seems to me this will work better with a human agent in charge.

3. Feedback about self-regulation. Here it gets even more interesting. This kind of feedback is about neither the product nor the process, but about how the students view and/or make judgments about their product or process. This "addresses the way students monitor, direct, and regulate actions toward the learning goal." This sort of feedback can motivate students to want your feedback. Very simple examples: "What do you think about your progress so far?" or "Show me how you're coming along," or "Do you feel like you are getting better at this?" followed by, "What makes you think so?"

If you ask a learner if they believe they are getting better at a task, what do you generally get back in response? In my experience, it's something like, "Yes, I think I am improving. What do you think?" And what just happened there? The student is suddenly asking for your feedback. They are asking for input. This puts them fully in charge of their learning and their outcomes. It makes the specific feedback, whatever it is, all that much more powerful when it comes. Effective learners always have sharp self-assessment tools--and they can be sharpened through "Level Three" feedback.

Level Three feedback can easily be provided online. I would not attempt to automate it, but it really boils down to asking learners for some self-reflection. This can be as simple as: "Write a paragraph reflecting on your progress." (Getting learners into the habit of thinking about their learning strategies is another research-supported design element that can improve learning greatly.)

4. Feedback about the self. Here's a somewhat counter-intuitive level. If each one of the levels is more effective, done well, than the previous, and each one gets closer to self-motivation and self-efficacy, closer to the self, you'd think that this fourth level would be the pinnacle of effective feedback. But it's just the opposite. "You're a good learner," or "You're one of my best students," or "You have a knack for taking the wrong tack," are all bad feedback strategies. Why? "Praise addressed to students is unlikely to be effective, because it carries little information." (Hattie and Timperley). And in fact, praise can be demotivating. The learner reaction goes something like this: I thought it was about what I was learning, the goals I was achieving, and then you made it about me. I don't want to be your favorite, that doesn't motivate me. I just want to be good at this. When we make it about them, we also make it about us.

It has also been demonstrated, and logically so, that another way feedback can be demotivating is if the underlying message is that success comes from some natural state, such as being bright or sharp or old or young. The better message is that success comes to those who pursue it (see Carol Boston on The Concept of Formative Assessment, for more on this). "Hard work gets you to your goals," is a message about the process and the product, not about the learner.

Good news: Level Four feedback is very easy to avoid online!

So here's a little meLearning. Not only can lack of feedback hurt my learning efforts, the wrong kind of feedback, though well-intentioned, can hinder them as well. And the right kind can provide a serious uptick in both outcomes and learner motivation. All this resonates with me, and motivates me to refocus on the feedback loops in my eLearning product. Hope it does the same for you.

How much should eLearning cost? Less.

The downward pressure to keep costs low is universal, whether you're talking higher ed or corporate training or eLearning as your product. The reasons are not all economic. There are expectations, I believe, rooted in natural but often unexamined assumptions. If you could tune into the internal monolog of your CEO, CFO, President, Provost, you might hear something like this:

"It costs what? Are you kidding me? I can pay a knowledgeable, competent person a couple of thousand dollars to develop a course and teach it in a classroom, and they're glad to have the money. Why do I need to pay ten times that amount to put the same thing online?"

Maybe that's not an internal dialog in your world; maybe it's painfully external. Regardless, the question is, what should it cost? And if it really costs 10 or 20 times as much to put it online, why does it cost so much?

I've developed a little chart to help explain what's happening here. Not to explain the cost of instructional designers or learning management systems or multimedia or video streaming. It's to help developers think about where they put their money. Because the reality is, when you decide not to invest in development, you are deciding to invest in delivery.

Take a look. What Line 1 says is that if you spend very little on development, the way you do when creating a face to face class, you're going to end up spending a lot on deployment, on delivery, unless your target audience is very small. Repeating that class over and over, paying trainers, faculty, maybe travel days, airfares... these costs become enormous over time. And if you just throw the course online for low costs, using the old "shovelware" approach, you'll pay through the nose for support costs and redevelopment, not to mention attrition.

Line 2 tells you the opposite. If you spend more on the development, creating it the right way online, you can deliver it to a lot more people a lot less expensively. And of course, a lot more consistently.

So you make the choice. Making it with eyes wide open means that you can and should choose your model, and adjust both the development and delivery costs to suit your needs. The classroom, Face-to-Face model gives you the lowest costs for development. The online, Self-Paced model gives you the lowest costs for delivery. Neither one is a good model for everything, but both are effective for something.

And then of course you can mix and match the models, building self-paced components into your online cohorts, or adding virtual labs or low-touch facilitation to your self-paced products.

My point is not that one particular model is optimal. My point is that if you are going to develop and deliver learning of any sort, you are going to spend your money somewhere. Spend it wisely up front, and you can lower your deployment costs and increase predictability. Don't spend it up front, and you are locked into the high cost of delivery.

What you believe affects how you learn.

The headline says, "Disbelieving Free Will Makes the Brain Less Free." And the story line is simple... get people thinking about the possibility that their own unique ability to choose is compromised by genetic determinism, and they will do poorly on a "readiness" test. There are several interesting questions to be asked here, and several profound implications for learning.

1. What you believe affects how you perform. Want to enhance performance? Want to change behaviors? Start with your learners' underlying beliefs. And not just any beliefs, but their beliefs about themselves--particularly the "I can't do that" sort of beliefs. Don't waste your breath teaching them what to do or how to do it if you haven't focused on who they are, or who they will be, once they have mastered the knowledge and skills you're teaching. They have to see themselves as someone who can and will and wants to go where you're leading.

That may sound overly philosophical, or even arrogant. After all, you're not in the belief business. But think about it. Coming to a new belief about yourself is not necessarily a big deal or an enormously difficult process. Take a close look at something that may seem impossible right now (getting that next degree or learning to fly a fighter jet or defeating the dragon-monster on level 6), and then focus on whether or not you can see yourself as a PhD, or a fighter pilot, or the master of that video game. If you can catch a new vision of yourself, you're halfway there. You're motivated to do what those sorts of people do. Like the Marine Corps says, maybe you really can be one of them, but you first must identify with the outcomes. That's all a change in beliefs means. Who you are always drives what you do.

2. Some beliefs are clearly more helpful than others. I don't want to be Machiavellian any more than you do, but the fact is that some people's beliefs drive them forward and some people's beliefs dry them up, shrivel them all into themselves. The genetic determinism of Francis Crick, which was the bedtime story inflicted on the participants in the study, is a mind-numbingly thorough proposition that we are only the products of our genes, and there's nothing we can do about it. Not only your free will, but your very consciousness, your sense of self, is "no more than the behavior of a vast assembly of nerve cells and their associated molecules." What you think of as being "me" is nothing but neurons firing. These kinds of beliefs are clearly not helpful if you want to accomplish anything in life--or to teach anyone anything.

Well, you may ask, so what? Truth is truth, whether it is helpful or not. We have a duty to believe what is true. Yes, of course. But without getting too far off the point, let me just ask, doesn't it make sense to seek truth in the direction of life, not stupefication? In the direction of activity, not helpless inaction? This world, our universe, everything we see and feel and know to be true, is bursting with life and activity. Traveling down some dark and lonely path, away from what is robust and fertile and sunlit and active, away from the endless possibilities of life, just because someone with a high IQ once said that the Truth, capital T, is to be found in that direction--that's foolish at best, tragic at worst. When in doubt, I say, go with what works.

And besides, it's your job to make it work.

3. You don't have to change someone's underlying philosophy to change their beliefs about themselves. I was privileged to lead the charge in building an online nursing master's degree program with a great team of designers, developers, and content experts. Our audience research revealed a startling fact: while most of the candidates wanted to move up, to make more money, to get off the floor where the hours are long and the work is backbreaking, they also felt guilty about it. Their shared value system, what it means to be a nurse, was tied up in being a care-giver, in advocating for patients. They feared that by becoming managers or educators, the two career paths opened to them by our degree, they would lose this.

So we spent the first part of the orientation course showing them that in fact their reach would be extended. Far from abandoning their mission, they were now on a path to expanding it. This simple effort, probably no more than twenty required minutes of a two-plus-year degree program, made all the difference. We addressed their identity. We gave them the opportunity to see themselves with a new, improved identity, having a greater impact by reaching more people than they ever could before. We showed them they could stay true to their original mission and then some. And we played that theme out through the entire program. Measure that nursing program how you will--enrollment, retention rate, student satisfaction--it was an enormous success.

One more example: the military. Why is military training so effective? In many ways it is the gold standard for training, whether it's complex and computer-guided, or grunt-simple, they seem to know how to do it all well. My belief? It's because of basic training. It's that six to twelve weeks of rigorous, sometimes nightmarish activity, the purpose of which is to make you a soldier. Or a sailor. Or a marine. What is that but a very careful reformatting of the identity? I'm not saying the actual training isn't great. I'm saying that soldiers obey orders, and when the orders are to learn something they learn it. This is why applying military training to civilian operations sometimes leads to less-than-stellar results. It's not the training so much as the people being trained. You and I don't get to start with 6 weeks of boot camp for all our learners (unless, of course, you do). But we can all tie whatever our learners learn into their basic belief systems.

So whether you are training people to put widgets together or educating them to generate ideas to save the planet, focus first on how they think of themselves. Let them see themselves as a widget master, or as an idea generator. Take the time to make sure they have fully identified with their own outcomes. It will pay off enormously. What they believe strongly affects how they learn.

The next wave of innovation in higher ed.

"An organization simply cannot disrupt itself," asserts Clayton Christensen and the authors of Disrupting Class---->. If you're going to innovate, really innovate in the way that iPods or PC's or online day-trading innovated, you're going to have to do it outside the usual boundaries. This, of course, is what the online for-profit universities did, working outside the traditional ivory infrastructure to reach a huge customer base that was absolutely not going to stop working, move near campus, and go back to school full time for that next degree. The traditionals didn't want those students, and so the for-profits went after them with online classes and office-park classrooms. The classic disruptive innovation cycle began. That cycle continued on its normal trajectory until last summer when the traditionals, with their governmental power base, turned on the for-profits with punitive regulations, most notably the "gainful employment" clause. If you can't beat 'em, regulate 'em out of existence.

That punitive effort, as has been stated here before, seems bound to crater. It's always felt a bit last-ditch to me, and now The Hill reports that it's in serious bipartisan trouble. It seems you can't take away from millions of Americans the best path to a better life that they have ever known, without creating an uproar. So the classic cycle of disruptive innovation rolls on, right? The innovators target a new market that the old guard doesn't want, provide it with a product that changes the landscape, then the old guard eventually embraces it or pays the consequences.

Except that something odd is happening in higher education. The for-profits have stopped innovating.

Reeling from the regulatory crack-down, many have spent their time, money, and energy fighting back with lawsuits and other legal maneuvering. But what is the basis of their legal arguments? If you pull back the covers, you find this: You're treating us unfairly, singling us out, and really, we're not any different from them. And what this means is that behind the scenes, the one-time innovators are scrambling to distance themselves from their innovative roots, straightening out any wrinkles that may make them look, well, unseemly (Innovation? Us? No, no, we're just like them!). Now you have former-innovators working hard to fit in, and to become organizations just like their peers. At least one for-profit that was actively fighting the "gainful employment" rule went full circle and converted to non-profit status earlier this year. If they can't beat you, join 'em.

So if an organization simply cannot disrupt itself, what does that mean for higher ed? It means opportunity for some new innovators.

Did you know that Compaq invented the iPod? Or rather, the first palm-sized digital "jukebox" with enormous storage capacity? I just learned that, thanks to an article I stumbled across in C-NET Reviews. Compaq beat Apple by 3 years and still lost in the marketplace. Compaq was simply not prepared to make their own innovation a centerpiece of their business strategy. Apple, fully familiar with the idea of making the most out of someone else's invention by perfecting it, and its business model, was well prepared to launch into a business that was not originally theirs.

So who will the new innovators in higher education be? Who are those who are watching all this unfold, and are ready to take what has been done so far to the next level? I had lunch once at a conference with two of the product people who worked on Apple's iTunes/iPod system. "We couldn't believe Sony wasn't already doing this," one of them said. "We were in a hurry," the other chimed in, "because we thought that before we could get our product to market, one of the big entertainment/technology companies would already be there." Apple couldn't have been more right about their product, or more wrong about their competition. Not only was Sony not there, the media giant and one-time innovator (remember the Walk-Man?) would line up on the other side, working to protect their portfolio of artists from the revenue squeeze that the mp3 revolution brought about.

The new innovators in higher education are not in the spotlight right now, but they are not on the sidelines, either. They are working hard as all this plays out. They have accreditation. They understand in ways that most of the original, big-name for-profits never did that quality is key--educational quality, product quality, business quality, and academic rigor. Like Apple, they understand that perfecting the business plan and the product means huge opportunity. Blackboard and streaming lectures are 1990's technologies. The future is differentiated learning, using the power of technology to mass customize education and prove outcomes beyond a shadow of a doubt.

They're waiting. But knowing how innovators tend to think, you can bet they won't wait for long.

A better business model than the shell game

It doesn't have to be a full-on, for-profit business model, it just has to be better than the current shell game. Inside Higher Ed reports that a number of state governments took stimulus money in 2009 and poured it into higher education, while actually cutting higher ed budgets. And those cuts are going to be exposed very soon.

The stimulus package "opened up the ability for states to reallocate dollars away from education and mask it with federal money." Why did they do this? Because overall budgets were crunched and the feds were offering windfalls for education. It seemed good to state lawmakers to take their own local tax revenues and redirect them into budget areas that weren't being so lavishly supported by Washington. A shell game? Robbing Peter to pay Paul? Call it what you will, but don't call it a sound business plan.

I suppose it's barking up the wrong tree, or perhaps the wrong tower, to make the modest suggestion that universities (and state legislatures) might examine their education revenues and plan ways to increase them without relying so heavily on taxpayers' dwindling dollars. I understand the monumental nature of this suggestion, but I also know that there are places to start. Like, perhaps going to online options that can actually compete with the online, for-profit brands.

After all, the for-profit schools have managed to do well enough with a model that creates a positive cushion between expenses and income, even while growing. Yes, growing! The state schools (surprise) lose money on every student, so when their budgets are cut, they have to consider reducing enrollments. Unlike anything at all in the private sector, the solution is not more paying customers--it's fewer. Think about that a moment, and take it to its logical extreme: State schools would be at their financial best if they had no students at all. Amazing, but unfortunately, quite true.

Any business model improvement would be a positive one for the university system, and for our economy, and for our wallets as taxpayers. As it is, some mad scrambles are ahead for many university systems. Maybe someone, some brave soul somewhere within academia, will think about the free market as a possible solution. And if not, maybe a legislator or two will speak up?