Food for Thought
Imagine if someone said to you: “Oh I gorged myself for four years back in the eighties. I ate so much then that I don’t have to eat ever again.” What would you say to them?
Some people are thin, others are fat. Some eat healthy, some not so much, but all of us need to eat every day (give or take a day or two) in order to survive. No one can live, let alone thrive, if they ate for the first twenty years of their lives and then had to starve themselves.
Why is education any different? Why do we believe that education stops (for most people) at age 17 or 21 and then we have to survive on what we learned then for the rest of our lives?
Actually, very few of us believe that education stops at 21. All of us understand that we learn continuously, throughout our lives. In some professions — academia, music, high technology — continuous learning is encouraged by the profession itself. Still, even in these professions, we don’t necessarily learn how to learn. For the most part people stick to a narrow, disciplinary idea of learning. Rare is the scientist who learns an entirely new area after they are tenured. Disciplinary learning is important, but it’s not enough to address the complex challenges of the future.
Let’s go outside the learned professions and see what curious people, especially children, do when they want to learn something. What they do is closer to play than to work. Making new things is fun, even when the new thing is an abstract commodity like knowledge.
The idea that learning is making knowledge isn’t new; Socrates knew about it when he called himself the midwife of wisdom. These basic human qualities — curiosity, questioning, dialog are still at the foundation of learning, except that we now have technology to amplify, aggregate and distribute learning across vast numbers of people. How do we make use of technology, while building on our natural, human capacities for learning. That’s the challenge.
People + Technology → Continuous Personalized Learning
Let us now look at some major shifts that a continuous personalized learning model entails. How can we build a lifelong learning society?
Lifelong learning societies
First, it’s clear that continuous learning cannot be learning removed from society. We cannot sustain a world in which everyone’s a full time college student from the time they are born until they die. We have to be producers as much as consumers of knowledge.
Lesson 1: Lifelong learning societies will mix work and learning throughout their citizens’ lives.
Second, it’s not clear that being a full-time student is the right thing — as we are discovering in the cognitive sciences, our mind is both embodied and embedded; we have minds precisely because we are embedded in a world where those minds are put to use. Natural learning, i.e., learning that happens as a matter of course because we are hardwired to do so (examples: learning to walk, learning to see, learning to speak) is based on tight feedback loops from mind to body and world and back. That sensorimotor loop is crucial; we can’t separate out the learning from the feedback loop. Why should artificial learning, i.e., learning that has to be taught explicitly in school and college, be any different? We should embed explicit learning into the same feedback loop of knowledge, practice and mentor feedback. Musicians and monks already behave that way. The rest of us should ape their behavior.
Lesson 2: Just as real reporting requires embedded journalists, real knowledge requires embedded students.
Third, once we step away from theoretical knowledge, for which we go to university, and look at the distribution of expertise and wisdom in all its forms, it’s clear that knowledge is spread throughout society. Our collective ability to aggregate distributed wisdom has been rather poor — most of these knowledge networks didn’t write books, and the libraries of the world were built to satisfy the demands of professors, not the universal learner.
The internet gives us the ability to aggregate human wisdom at a new scale, and to do it in a manner that enables different modes of expertise to coexist. Why should I choose between learning statistics and self-transformation? Why can’t I engage with a full spectrum of human wisdom from diverse sources, driven by distributed networks of mentors, peers and learning media? I believe that a new era of learning is well within our reach.
Lesson 3: Use technology to aggregate wisdom from all corners of the world, high and low.
However, in order to do so, we need to look beyond the MOOC, which is the last gasp of a one-way, top-down model of learning where the elite instruct the masses