Current Issue
This Month's Print Issue

Follow Fast Company

We’ll come to you.

6 minute read

Going From One-Size-Fits-All Education, To One-Size-Fits-One

We need to teach children individually, and in a way that doesn’t emphasize memorizing the right answer, but more realistically reflects how we learn and succeed in the real world.

Going From One-Size-Fits-All Education, To One-Size-Fits-One

In June of 2009, after Michael Jackson died, I decided it was time to learn how to moonwalk. I went to YouTube and found the "How to Moonwalk" video with the most hits, a simple 2:15 minute homemade job by Montreal DJ AngeDeLumiere. The video proved to be a lesson not only in a dance step but in transformative pedagogy.

Ange begins by showing us what we think is the way to do the moonwalk. He’s right. That is exactly how I used to think it was done. He then demonstrates the results of your intuition, a dorky backwards walking that looks nothing at all like the elegant optical illusion perfected by the King of Pop. "That’s all wrong," Ange admonishes us. "You don’t want to do that." Then, he shows you the right way, breaking it down, explaining the movement, the weight shift, which heel is doing what while the other foot is doing something else. He shows you slowly, then more rapidly, until, before your eyes, AngeDeLumiere is moonwalking. A few weeks later, so was I.

Alvin Toffler calls this method of instruction "unlearning." In times of dramatic change, when your old habits are preventing you from succeeding against new odds, you have to first see what trouble your old habits get you into. Before you can move forward, you have to see your best intuitions, skills, and patterns not only aren’t helping you move forward; they are what are holding you back. Proceeding in a new environment on old intuitions makes you seem (to continue the moonwalking analogy) like a dork walking backwards. Don’t do that!

Ange’s video is a great model of teaching and a great metaphor for the kind of educational change we need to embrace right now. We think teaching looks a certain way: students learning from teachers and then using high-stakes subject-matter standardized testing (Kindergarten through MCATs for medical school) to measure who is best. That’s basically how we’ve been teaching since the multiple choice test—which was explicitly designed to run students through the classroom as fast as possible during the crisis of World War I—was invented in 1914. It’s well suited to the standardized, top-down factory or corporate model of the Industrial Age. Schools did a very good job of training a certain compliance and complacency and measuring who did best at an extremely limited number of intellectual tasks in that environment of controlled instruction.

But if learning is the issue—and especially learning in an age of information abundance—then we have to unlearn that old model. It is holding us back. No research—none—on how we actually learn a new skill outside the classroom supports the practices we have institutionalized in our schools. We do not learn the vitally important skills we need in the world by all learning the same way, in a lecture model, and then being tested at the end of the course. One-size-fits-all learning really fits no one particularly well. Great learning is almost always one-size-fits-one.

Take the example of learning a new sport. If I take up tennis, I don’t want a series of static lessons or lectures (either online or in person), and then a score at the end. I want a teacher who shows me, corrects me, plays against me, challenges me, shows me again, corrects me, whoops me once more, and on and on until I can play with partners who challenge me to excel in the same way. That seems common-sensical, yet we send our kids off to school for 16 years on an educational model devised on the idea that you put them all in a room, talk at them, and then test them at the end by a standardized series of "best answer" questions that weren’t even written by the person who tested them. There’s a mismatch between content and the challenge, the score at the end and the exploratory, expansive, "search and find" world of learning that exists online or in the world of real-life employment where one is constantly tested and then needs to experiment to find the best methods, partners, and new skills to meet the challenge.

Whenever I speak before large gatherings of corporate trainers, they tell me they can recruit anyone now, in this economy; the very best students from the very best universities. And they are dismayed that it takes a minimum of one to two years to retrain them from being "great students" to being "great colleagues." These new employees are so used to getting the perfect score on the test at the end of the course that they themselves do not know how to self-correct or how to take mid-course correction from others. They have had 16 years of an education in choosing the best from among four answers to simplistic questions, capable of being answered in only one way. Not a lot of life works that way. Most of what we do is precisely about learning as we go, practicing, breaking old habits, learning something else, admitting what we do not know, finding someone who does, getting feedback on a work in progress, failing, trying again, failing even worse, trying again, and so forth. There is no end-of-grade test, there is no grade point average. There is a lot of unlearning and relearning how to learn, over and over. Like a tennis lesson. Not like our formal systems of education and their high-stakes methods of routinized, standardized assessment for "excellence."

We are starting to get online classes that are modeled not on formal learning but on the most challenging informal learning. The fabled statistics course offered by Carnegie-Mellon’s Open Learning Initiative, a free and open online educational enterprise, teaches probability or statistical reasoning through a series of lessons that incorporate explanatory content, learn-by-doing exercises, "Did I Get This?" activities that allow you to self-check your own understanding, supplementary material designed to spark interest in why you are learning what you are learning, and then checkpoints or graded exercises that allow you to see how well you are doing. To be fair, that is more interactive than far, far too many existing statistics courses being taught out there by a prof who spends more time scratching on a blackboard than finding the best way to inspire his students’ statistical reasoning.

Even more exciting, Khan Academy has some of the best artificial intelligence (AI) learning scientists in the world studying what people do and don’t get the first, second, and third times from the massive collection of instructional videos on subjects ranging from algebra to art history. The hope is that, by gathering operational examples from what is now millions of learning exercises, future students will receive highly customized, individualized learning instruction geared to their particular habits—and even able to point out bad habits and offer specific corrections to them in order to accelerate and deepen learning.

I do not believe that online learning will ever replace individualized instruction. As illustrated in the "cartwheeled classroom" of the Haiti Lab that I discussed in my last piece, there are forms of engaged, relevant, entrepreneurial theory-into-practice experiential learning that no computer can begin to challenge. At the same time, the best online learning does challenge the one-size-fits-all standardized model of education and assessment that has persisted for almost a hundred years and that no longer serves the world in which we all now live and learn. We desperately need to unlearn fundamentally wrong pedagogical principles about the role, function, and methods of formal education before we can begin to learn a better way.