We live in a culture obsessed with learning. We are told that learning is the answer to our problems: we have to learn to love ourselves. We have to learn new skills to meet the needs of the New Economy. We have to learn how to find romance and friends in the digital era. We have to learn to live with the realities of global warming. To live, we must learn. And of course in the 21st century, the list of things to learn has grown and grown, and continue to grow exponentially. We’ll never even learn all the things we need to learn.

But like so many words that are used with frequency and enthusiasm–like, say, democracy–it seems to me that “learning” has become a superficial and vague term. What do we really mean when we talk about learning? And do we all mean the same thing all the time? If not, then all our talk about learning might just be a lot of heat generating little light. So what is learning?

Of course, a broad term like learning has many meanings, as it should. Our goal here is not to narrow it down to one “correct” one, but rather to identify some of the different meanings. Because if one person intends one meaning while another understands a different one, then they aren’t really communicating. It’s that kind of scenario, where two people are using the same word in different ways, but without realizing this, that we need to avoid. As I have said before, if I say “dog” and you understand that to mean a furry, four-footed mammal that barks, we are probably on the same page. But if you understand “dog” to mean a thing with feathers on two feet, then we probably won’t communicate well. Such a misunderstanding around the word “dog” is, of course, rather unlikely. Unfortunately, I think the word “learning” is more vulnerable to vagueness.

As I said above, “learning” has a wide diversity of meanings, connotations, and specific nuances in various contexts. One could no doubt write a book on them. Today I want to just focus on the two meanings that I think are most common, and explore the importance of the gap between them.

On the one hand, learning very often means simply adding a new bit of information to one’s memory. “Dogs are mammals.” “Ice is frozen water.” “Canada is in North America.” To learn, in this sense, is to come across a new statement that one basically just adds to the “pile” of one’s knowledge. Much of our time in school, perhaps, is spent simply adding to this pile. And it’s worth pointing out that to be considered a relatively educated person today, we have to know quite a lot. The pile has to be pretty big. We expect schoolchildren to know all kinds of facts about history, about astronomy, chemistry, physics, about music. There’s a lot to know, and so it makes sense that we spend much of our educational time adding to the pile.

So this understanding of learning is important. But I think it’s a bit limited. I’m not sure this captures everything we mean when we talk about learning.

First off, if we take a moment to really explore any of the example facts above about dogs, ice, and Canada, we will see something curious. I can’t actually add any fact to my pile. Each new fact has to already have a connection to my pile in order for me to place it there. For example, if I tell you that “Canada is in North America” but you don’t know what “Canada” or “North America” are, then this statement is meaningless to you. Likewise, if you aren’t familiar with dogs or mammals, then telling you that “dogs are mammals” doesn’t help you in the slightest. You have to already be familiar with at least one of the terms in order to really learn anything from the statement.

New information, then, always builds on old information. That may seem obvious, but it’s important, because the “pile” model of learning presented above tends to assume that learning happens simply by presenting lots of facts to students. Certain education systems prioritize funneling huge amounts of information to their students as quickly as possible. This is especially true in certain cultures or disciplines; many are aware of the high-pressure, memorization-focused education systems in places like South Korea and Japan. Interestingly, they share a lot in common with the post-graduate education of lawyers and physicians here in the US: the focus is on memorizing a huge bank of facts that can be drawn on later.

But if it’s true that each new fact can only be learned to the extent that it connects to the facts already known, such a funnel-the-facts education model may be problematic. For one thing, the order the facts are presented in would end up making a big difference. For another, unless each individual student has the same pile of facts on day one, then the facts that each student can learn will actually be different. And yet curricula are not (and, realistically, could not) be tailored to meet each individual student. It could be the case that the conditions for good learning are just too subtle for any large educational institution to meet.

But this recognition that new facts can only be learnt when they can connect to the pile of already received and recognized facts should, upon some reflection, lead to a deeper point. How does the pile begin to be formed in the first place? And is the pile really a “pile”–that is, a more or less disorganized mess of facts? Is that really how our brains keep and access memories?

These questions should lead us from considering the object of learning–new facts–to the subject or agent of learning–the student. And this shift brings us to the second major understanding of the very term “learning”, I think. Here we are not concerned with each individual fact, but rather the structure or system in which all these facts are placed–that is, the mind that knows, recalls, and uses the facts.

We already touched above on how a new fact can only be learned if at least one of its terms is familiar to the learner. But this isn’t all. If we compare two learners, one who knows each term in a sentence, but not well, and another who knows at least one of the terms very well, their learning will actually look rather different. Imagine one student who knows that North America is the continent that the US is on, but not much else about its geography, history, geology, etc. Imagine another learner who knows a lot about the human history of the continent–knows about slavery, about colonization, about the diverse cultures of Native Americans, etc. For this second person, learning that Canada is also on this continent will mean much more to them than for the first learner. Immediately, the second learner will make connections and form new questions that the first learner could not: did Canada have slavery? How did Canadian settlers interact with Native Americans? When did colonization of Canada begin? They can ask these questions because they are already familiar enough with the term “North America” to know that these questions make sense to ask. To see this point more clearly, just consider whether you would ask the same kind of questions–about slavery, colonization, etc.–if you were talking about dogs or ice. Would it make sense to ask if frozen water had human slaves, or ask about dogs’ policies on colonization? Having a deeper knowledge about a subject makes one’s learning more about that subject easier and richer.

What I think this shows us is that our “pile” of facts isn’t a pile at all. It’s a complex system of connections. We don’t really keep a sort of mental rolodex filled with trillions of abstracted and separate factual statements. Instead, we organize our knowledge around concepts, and we integrate new facts according to the concepts we already have. Instead of a long list, our concepts are like a big cloud, with each concept able to be connected to dozens of others either directly or indirectly. So if I learn that Canada is in North America, and I already have the concept “North America”, I do not simply remember the sentence “Canada is in North America.” Instead, I relate this new concept of “Canada” to my previously-received concept “North America”, and I enrich this latter concept with new meaning. I have a complex system of concepts and their connections, and new learning is integrated into this system.

So far, so good, you might say. Perhaps we now have a better way of understanding how to “funnel facts” onto the “pile”. Seeing the facts as opportunities for new conceptual connections to be made within the “pile”–which is actually not a pile but a complex system–may allow educators to better hone their techniques for delivering as many of these opportunities to connect concepts. But there’s more here. Once we see that knowledge, that thinking, is a complex system of conceptual connections, we can begin to ask questions about its shape, its structure. When we thought of our knowledge as just a “pile”, then such questions made no sense. The pile simply needed to be bigger. But once we see that knowledge is a sophisticated structure, then we have come to understand it better.

Now seeing students not as piles of facts, but rather complex systems of conceptual interrelation, we might ask whether all such structures are equally effective or healthy. We might come to see that sometimes, what we want a student to gain is not a new fact to add to the pile–er, system–but rather we may want the structure itself to change. This is learning as transformation.

If we picture concepts again, and we bring to mind a vast three-dimensional cloud of concepts which can connect to many dozens of nearby concepts, and through those connections connect to even more distant concepts, we can imagine different ways of arranging those concepts. Depending on how many connections each concept has, and which other concepts are closest to it, and the overall shape of the whole cloud, different kinds of learning might be easier or harder. For example, if each of our concepts only connects to one or two other concepts, then new learning will be more difficult. Most new facts will involve a long chain of concepts connecting and connecting. So a new statement will be murky and difficult to articulate. On the other hand, if each of our concepts has a direct connection to a dozen, or two dozen, other concepts, then new learning will be comparatively easy. The number of connections we would have to follow to arrive at new learning will be fewer, and thereby quicker, easier, and clearer.

Likewise, if we imagine our cloud as a long sort of line, perhaps only a few dozen concepts across, but thousands of concepts long, we can see that trying to move from one end to the other would take many thousands of connections. So concepts on either end of our “cloud” will be hard to connect. On the other hand, if our cloud is more spherical, than all the concepts will be relatively close to one another, and so, again, connections will be quicker and more direct.

Of course such a discussion of “shape” is basically metaphorical (whatever relationship it may have to neuroscience is completely beyond the scope of my knowledge). But I hope that this discussion captures something crucial: the way our system of concepts is arranged, organized, and connected will greatly affect how well, quickly, and clearly we can think. If the first kind of learning is simply tacking on new concepts–perhaps to the outside or periphery of the cloud–then the second kind of learning is more radical. It involves reworking, remapping the cloud so that its member concepts are closer together and more densely, richly connected. This is what we might mean by the second kind of learning, learning as transformation: sometimes, we want to teach students not what to think, but how to think better.

Of course, doing so is no easy task. But I think it’s important to keep this distinction in mind when debating K-12 educational policy, for example, or the role of colleges and universities. It is common today for many to talk about education as only worthwhile to the extent that it gives students information or skills they need to find work. But while this is no doubt very important, it may miss the second kind of learning, transformational learning. It may be the case that to tackle some of the issues that will be most pressing for us in the 21st century, we humans will have to not just add facts to the pile, but rather learn new ways to think. It may be also be the case that we will have to re-learn older ways of thinking that have been lost over the past few centuries if we want to discuss certain topics–ethics and theology come to mind.

In any event, my goal is not to necessarily privilege one kind of learning over the other–both are important–but to stress that if we are going to discuss or debate something as important as learning, we need to make sure we are really talking about the same thing. Trying to talk with unclear terms is like measuring in inches and then building in centimeters: a confusing mess, and sometimes even a disaster.