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Learning About Learning 

Common Terms and Concepts in the Field of Learning

(For A Glossary of Common Learning Terms click HERE)

John Webster

I. Learning in Life vs. Learning in School

As human beings, learning is one of our primary activities—up there with foraging, mating, playing, and working.  We start learning at birth (some suggest we’re doing it even before we leave the womb), we learn at fantastic rates through our early years, and we keep on doing it as adults pretty much up until the end.  Which makes a second point about learning:  we tend to think of it primarily in educational settings, but in fact we are learning like crazy all over the place. 

Of course, educational learning is not the same as much of the other learning we do in a day.  For one thing, while we want educational learning to last as long as possible, we learn many other things for relatively short—sometimes very short—periods. My mind, for example, tracks how much coffee is left in my cup over the course of an hour or more, but by late afternoon, well after the coffee is gone, I will not remember how full my cup was at any given point. We experience a similarly short retention time while driving, when we pay attention to where other cars on the road are, “learning” (which really only means “storing in memory”) for a short time their positions relative to our own, a learning that is continually being updated as our car’s position changes. Indeed, one mark of a good driver is (among other things) an ability to keep relearning his or her position relative to other cars on the road nearby. 

So while a lot of our real life learning is indeed long term (think about song lyrics from groups 10 or more years back), much of the learning we do in a day is very short term, a kind of “temporary learning,” every trace of which is gone by the time we put the car in the garage—something we would not like to say about what we learn in school. 

But beyond its duration (what learning theorists call “retention”), there is something else about academic learning that is very different from what you might call “real-life learning”:  a lot of it occurs in settings far removed from any real world application, and a lot of it is from books or teacher talk, not from something we are physically or emotionally involved with.  Indeed, because much school learning is remote from the daily interests and needs of students, many find it difficult to stay interested in the learning process.  People of any age can be bored or confused by school learning, and for a wide array of reasons.  We may have other things on our minds that seem more important, or we may not see the point of what we are asked to learn, or the material we are asked to learn is too complicated to engage successfully.  Why spend hour after hour attending in class or hunched over a textbook when the reasons we are given for doing so (“You’re going to need this someday!”) seem artificial and unbelievable?

Which brings us to one more thing that makes school learning different:  for the most part we have to study it to learn it.  We don’t, for example, actually learn much from doing a single long division problem since without a great deal of repetition few of us would remember the process.  If we are to retain the ability to do that process, we’ll have to practice it over and over again—often for years. 

So school learning is for most students both quite different from life-learning, and much more problematic.  Unsurprisingly, then, educators have given much thought both to how best to teach various subjects and, more recently, what it is inside learners themselves that actually enables them to learn.  What follows in Part II of this is an introduction to what has been learned over the past 20 or so years about how, in fact, we human beings learn, and how we can make our learning better.

 

 
 

II. How We Learn

The key elements of learning involve perception, thinking, and memory.  Some learning comes simply from perception and seems automatic—you see something, your mind somehow marks it as worth remembering, and it gets stored in long term memory where it stays for a lifetime. Other learning is anything but automatic.  You take in an idea, a bit of description, a reading, a lecture, you may even understand it, but then within a few days or weeks it just seems to have vanished. 

School learning often feels more like the second of those processes than the first. Yes, sometimes we read, see or hear things in school that we remember clearly and well. But much of school learning seems to require an enormous amount of effort first to understand at all and then to remember. Most of us would like to be able to learn more and to remember what we learn longer, and those of us who are teachers would like our students to do the same.  But figuring out how best to promote learning is actually quite difficult.  Still, a few things about the mechanisms by which we learn are clear, and I set them out here as a way to start thinking about how we can develop more effective ways of using them to learn better and with greater retention.   

New skills or information we perceive by reading, seeing, or hearing first go into what cognitive scientists term the “working memory,” a kind of memory different from our “long-term memory.” 

Generally speaking, we actually have two kinds of memory: working memory and long lerm memory. Working memory is a kind of scratch pad in the brain, except that its contents are of relatively short duration—often only a few seconds. Long term memory, as the name suggests, is the sort of remembering we mean when we say we have "memorized" something. Most of our new memories begin by entering our working memory; once there our brains in effect make a decision about whether or not to remember them for the long term. Most things that enter working memory are not in fact sent to long term memory. They include what you saw when you looked out the bus window on the way to work, or what passed through your mind as reflections on the walk from the bus stop to your first class. But they also include problems from your math homework or processes you are trying to master at work or at school.

Ideally, the things our working memory decides have value are then transferred to our long-term memory, where they reside until we need them to accomplish one sort of task or another. So, in the best case, perhaps we read an explanation of “marginal profit” in an Economics text, we store it in working memory as we connect it to various things we already know, we decide that we understand it, and we then remember what we have just “learned.” Ideally, we will then be able to recall the concept whenever we need it.

That would be, as I say, the ideal, and it often happens. But not always. Perhaps the main challenge to that ideal is the fact that our working memories are quite limited, both in terms of the speed at which they work (relatively slowly) and in how much we can store there: although we have thousands of pieces of information and procedures in our long term memory, in our working memory, by contrast, we only have room for a very few ideas/items at one time—5-8 max for almost everyone, and even fewer when other things are on our minds at the same time.

That fact surprises most people, but the research on this is amazingly consistent. To test your own working memory’s capacity, look at the row of numbers below for 3-5 seconds, then close your eyes and try to repeat them aloud.

4 9 3 0 2 1 5 6 7 5

Few of us can actually do this trick—10 numbers is more than most human beings can hold in working memory at any one time. But even if you managed to get those 10 into your working memory, they are unlikely to stay there long, and, in fact, will very likely be gone by the time you have read this sentence. (To test that claim, without looking back at the sequence, re-close your eyes and try to repeat the number string again.)

If you can’t remember all the numbers, don’t feel bad. Almost no one can do this because your brain will not actually have done the work of uploading that string of numbers into your long-term memory. Instead, because your working memory is very short-lived—often only a few seconds—simply paying attention to making sense of the next sentence you read will have forced your mind to clear your working memory, and, along with it, any ability to repeat the numeric string.

All of that said, while your working memory is limited in its ability to retain information, it is still important because it is the doorway through which most of your school learning enters your brain. You take in a fact, you process it, and if you think it has value you silently ask your brain to remember it. The work the working memory does, then, is processing and evaluating and, if appropriate, sending new learning along to long term memory. (You can more accurately test the limits of your working memory at:  http://cognitivefun.net/test/4

A different limit on learning is that using your working memory requires "work." Surprisingly, this is very different from most of our thinking. Much of what our brains do requires almost no conscious thought, and our brains do what they need to do with amazing efficiency and very little sense of strain. Take a walk in the woods and your legs may get tired, but your brain feels great—even though it is processing huge amounts of information via your sight and other senses. Particularly impressive is your ability to manage your motor functions, calculating and coordinating dozens of muscles as you stride along the uneven and bending path. That is a lot of mental activity, but because it is a kind of thinking that you have done thousands of times before, it takes almost no energy or time to do it well now. Indeed, after such a walk you may declare that although you are physically tired, mentally you may feel more relaxed than when you first set out!

By contrast, using your working memory can require concentration and focus, and one reason a student may dislike or resist having to study is that the work of conscious thought is something that human brains often want either to minimize or (second best) to be rewarded for doing.  Thus, because it actually takes a lot of energy to use one’s working memory, a learner will often feel a need to take study breaks, eat chocolate, or go do something else less stressful.

One other limitation of our working memory is that it's not very fast—indeed, some psychologists call it "slow thinking" to differentiate it from the routinized knowledge you have stored in your long term memory. Unlike the fast-thinking speed at which the brain processes light coming into your eyes and instantaneously creates in your mind a "picture" of what it is seeing, your working memory often has to "think something over" or "consider" or "evaluate" things—sometimes for seconds, at other times for minutes or even hours.

To experience in a simple way how this slowing down of thought occurs, consider first what happens when you do simple multiplication.  Suppose you are asked in a math class to multiply 2 by 2, or 6 by 5, or 8 by 9.  You have memorized those answers and you are thus able to respond instantaneously even though the first time you tried to do this you probably took a while to figure it out, perhaps (like my 4 year old granddaughter!) by counting on your fingers. The fact is that most of us are drilled in simple multiplication so early and so often that by the time we are in third or fourth grade our working memory can retrieve the right answer from our long term memory in an instant.  That is very fast thinking indeed. 

But now suppose in that same class you are asked to multiply 36 by 21.  The answer to that is not in long term memory for most of us, and so your brain will now have to use its working memory first to ask your long term memory to supply what it knows about multiplying, and then, depending on what you’ve stored there from your elementary school days, to recall that 1 x 36 is 36, and that 2 x 36 is 72, then go on to remember to add a zero for the tens column, and then, finally, you need to add 36 to 720 to come up with 756 as the answer. 

Now, to be sure, many of us can do that problem in our heads, but very few will be able to do it instantaneously.  Still, since the problem is relatively simple, our working memory, making use of its ability to recall information from long term memory, can enable us to solve the problem, even if we do so relatively slowly. 

But then there are other problems that we cannot solve in working memory at all because there are too many items to keep in mind at once. Imagine, for example, that you are asked to multiply 3519 x 46779.   Almost none of us would be able to do this problem in our heads even if we were given an hour to do so, and the reason for this is that there are now so many numbers involved that we will run out of room in our working memory.  The basic math in the problem hasn’t changed—it is still multiplication—and the rules of multiplication are the same here as they were for the preceding two problems.  What is different is that we have more numbers to keep track of. That, in turn, means that our working memories become overloaded, and that’s enough to ensure that we can’t do the problem without the help of writing things down. 

So working memory is essential to our thinking, but it's also limited in several ways, among them that it is relatively slow. That said, the brain has actually developed some work-arounds for most of these limitations.

Although our brain's working memory is limited, our minds have ways to expand its capacity. Two such ways are routinization and chunking.

Routinization: As we have already suggested, the most common way we human beings can expand our working memory is by building up in advance a store of knowledge that can be recalled from long term memory when needed.  The mind does this by memorizing, obviously, and in many cases it can make what it stores more efficient by learning it so well it becomes “routinized” or “automatized”—by which we mean turned into an automatic routine with no slow thinking required at all

So, as is clear from the arithmetic problem outlined above, when you were a child learning to multiply you had to memorize the multiplication table, and what that really did was enable your mind to turn

5 x 4 = 20, and 14 + 14 = 28

into instantly recallable and useable routines.  For most of us these became routinized, and thereby available in an instant to speed us through what might otherwise overwhelm our working memory’s capacity.  What is sometimes called "rote" learning is actually an effort to expand our working memory's capacity to process new information by creating in long term memory a basic set of processes that function as effortless subroutines necessary to the learning of new and more complex matters.

Chunking: Another way to expand our working memory's limited capacity is to "chunk" information. Oddly enough, when we break a large idea into smaller parts, working memory will often treat each part's smaller parts as a single entity even when those smaller parts would otherwise each count as one of the 5-8 things our WM can keep in mind simultaneously. This chunking of information can thus enable us to handle a more complex task.

This is what happens when we make a mental note of a telephone number: instead of trying to remember ten different numbers we can break that sequence of numbers into smaller chunks—206, 555, 1234, for example—making it possible to remember fairly easily a 10 number string which, unchunked, one could remember only with great difficulty, if at all.

Chunking is thus actually the solution to the problem described above of how to remember a string of 10 random numbers:

4 9 3 0 2 1 5 6 7 5

As a set of ten numbers, few of us can remember that string. But if we turn it into three shorter chunks, the problem of short term memory becomes far simpler: 493-021-5675. Most of us can keep that in mind long enough to dial a phone, though five minutes later we may not be able to remember it again. Of course, we also are able to commit phone numbers to long term memory—a process made easier by the chunking built into the convention of assigning numbers in a three-chunk series of area code, prefix, and final segment. I myself know at least a dozen such numbers—you may know even more.

Among the most neglected of all methods of enlarging the working memory's capacity for dealing with new ideas and concepts is Writing.

If routinizing and chunking are important processes in problem-solving, the ability to off-load items from working memory by writing them down, and thereby off-loading them from working memory while still keeping them within the field of attention, is even more important. Some people think writing is just a way to communicate with someone at a distance, but that is simply not true. Writing is also a hugely powerful way to expand the reach of working memory and thereby expand as well our abilities to solve problems.

Hundreds, if not thousands, of times you have experienced the expansion of your problem-solving capacities that writing can enable when you have worked with math problems. Indeed, as I have suggested above, you have experienced it with almost every problem set you have faced in a math class since leaving 3rd grade. As with the complex multiplication example above (3519 x 46779), your working memory can't hold all those numbers at once, but once you write them down you can multiply one by the other quite easily.

In sum: what may be new here for many is the understanding that what writing can do for math it can also do for other kinds of learning: increase and make more effective the problem solving ability of your working memory!

For more on how expert writers use writing to boost working memory, go to Write to Think.

 

Metacognition as a booster of Working Memory:

In summary, one of the great challenges of learning is that we are in most ways quite unaware of how we have learned the things that we know. Superficially we may know that we learned a lot of Chinese vocabulary by studying lists of words, or by using flashcards, but we simply don't know how, exactly, those words finally stayed in our minds.  We can get some sense of it, however, by thinking (often via writing) in explicit ways about things cognitive science has identified as connected to our learning processes. I've described some of those things above; what follows below is a list of some of the most common phenomena that either enable or work against learning. One goal of this class is to see how to use these.

Thus in this course you will be introduced both to metacognition and to the process of metacognitive writing, and you'll learn as well a set of metacognitive tools that can increase your ability to engage and succeed with university level classes.

Finally, by enabling you to be more consciously aware not just of the particular elements of your learning but also of that new learning's connections to other things you know, strong metacognitive habits can greatly help you to develop your ability to transfer learning from one context to another. 

The Glossary below lists well-recognized learning phenomena, and I supply it to you as one step towards becoming a more conscious and intentional metacognitive thinker. Some of these terms arise in our course readings; all will be central both to writing your Learning Profile and to the research you will be doing for week 4's learning/writing conference. 

 

A Glossary of Common Learning Terms

(Some of the terms below have asterisks by them; those are concepts I think of as particularly valuable, but in fact every one of these concepts enters into just about every student's learning life.)

*Pedagogical Memories: When any of us think about ourselves as learners, one of the richest sources of information about our strengths and needs are our memories of ourselves as students. Sometimes it’s a comment on a paper, sometimes it’s a conversation with a teacher or with another student. Herb Kohl’s essay “I won’t Learn from You” begins with two of his pedagogical memories, the first of his “not-learning” in his Yiddish class, and later, his effort to cheat his way through his Hebrew class. Each of these memories is not only a good story, it is also something that when Kohl looks back years later he learns something both about himself as a learner and, more important, about how to become a better teacher.

These are “pedagogical” memories because they are of schooling, but they are also pedagogical in the sense that they enable Kohl to think back on a past event and, because he has become more knowledgeable a few years later than when still in school, he can see his experience through a different lens. Think of Kohl’s Hebrew class. As he remembers it he knows he behaved badly, but he also remembers that he experienced great pain and shame when the teacher made a fool of him—a moment of metacognitive memory that made him resolve never to shame the students he would go on to teach. With respect to becoming a writer, memories of praise have probably helped us build confidence, and memories of being shamed have made many students “hate” writing. But you are a different person now than you were in the 5th or 11th grade, so when we reflect on those early moments, sometimes we can change the way we think of ourselves and of our talents if, as adults, we re-see and re-understand what really happened.

We will ask you to do that here in English 108 in the hope that having brought metacognitive reflection to bear on your pedagogical memories you will be able to re-see and revalue some of your early experiences with writing. You can in fact think of every term in this glossary as a kind of conceptual tool to rethink and revalue your strengths as a learner and, especially, as a writer.

Long-term Memory:  The place in your mind that learning goes to live.  Some of what goes there will last a lifetime; other things have varying half-lives.  One goal of learning theory is to enable students to increase the duration and completeness with which they retain learning.    

Working Memory:  The place in your mind where conscious “thinking” happens. It is limited in its capacity, though its limitations can be minimized by various mental strategies, like routinization (or what some call automaticization), schemas, chunking and problem-solving writing (see Part II above and Writing to Think). Working memory is more or less co-extant with what we think of as consciousness.  I sometimes use what I call the “Three (or so) Things Rule” to talk about the limits of working memory’s cognitive capacity and the effects that has on our sense of difficulty. Three is actually a little low for how many new things one’s working memory can think about at once (it varies from person to person, but rarely gets higher than eight), but the important thing is that the capacity of working memory is quite limited, and, therefore, when learners come to material that is new to them, their efforts to hold a whole set of new understandings in mind at once may reach that capacity very quickly.

Trying to solve a problem that requires that you hold more things in mind than the working memory can manage creates feelings of difficulty, and that in turn can cause frustration, resistance, even anger. It can also lead to a decision that you just can’t solve the problem involved. Of course, thought about more positively, the feeling of difficulty can also be understood as a signal to slow down, look for connections to what one already knows, and ask questions. 

Routinization, Automaticization: These are equivalent terms for the speeding up of mental processes that results from uploading information from working memory to long term memory. Processes that have not been routinized are processes that still require working memory: the slow thinking part of our minds that we use to process things as we learn them (see the entry above). 

Fortunately, our brains are able to convert things we learn into automated routines which can be run with little to no involvement of the conscious mind. Every one of us has felt the difficulty that results from the limits of working memory, and we have felt as well the way that routinization of basic processes helps overcome those limits.  When you learn to drive a car (or ride a bicycle), for example, it may be difficult at first to manage all the steps required to put the vehicle in motion, and as a beginning driver it’s just as difficult (as my brother learned the hard way) to find the brake pedal. But after a few weeks or months of experience, new drivers not only run a car’s controls without much conscious thinking about them, but also know to check the rearview mirrors regularly, to check side mirrors when changing lanes, and so on. (The routinization process is explained in more detail above in section II.1.)

*Cognitive load: The degree to which the cognitive capacity of your working memory is full.  Our brains work easily with a few concepts or numbers at once, but when we work with more than three to five entities the “load” begins to get heavy.  Sometimes the heavy load can be exacerbated by having other things (like worry, anxiety or fear) also “on your mind.”  The need to spend mental energy to tend to those issues can increase cognitive load and thereby reduce your ability to process thought efficiently. (See Ramirez and Beilock, 2011)

*Prior knowledge/Preconceptions:  Everyone has learned things before they enter a classroom, and thus may bring to any learning situation prior knowledge or preconceptions—ways of knowing, “facts,” strategies, commonplaces.  Some of this prior knowledge is essential to learning: it is, for example, hard to learn calculus without first having mastered algebra. It seems obvious, in fact, that much learning becomes much easier when we already know something about whatever it is we are studying. Prior knowledge gives us something to connect new knowledge to, and because it has already been learned, it can help us remember more easily what we are learning.  (I like to think of prior knowledge as the sticky side of a mental Velcro© strip to which the tiny hooks of new learning can successfully attach.) 

That said, prior knowledge is not always an advantage. Just because we think we "know" something doesn't mean that that something is true. Indeed, there are times when we need to unlearn something in order to replace it with new knowledge. Thus the next term in this glossary is "unlearning"....

Unlearning:  This is the process one must undergo in dealing with prior knowledge that is wrong or misleading.  Unlearning is often neither straightforward nor easy, though teachers often assume it is.  Teachers may just say, “That’s the wrong way to think about it,” and then move on.  But that’s not always enough. People often have emotional and personality stakes in the things they have learned and the way they know them, and they may find themselves very reluctant to unlearn their earlier understandings. (The difficulty of unlearning prior knowledge is the subject of a 1987 video called “A Private Universe.” http://learner.org/resources/series28.html )

*Metacognition: Metacognition is thinking (often aided by writing) in explicit ways about how one learns and thinks. It is one of the most valuable learning strategies any student can develop.  One of the great challenges of learning is that we are in most ways quite unaware of what we know or of how we have learned it. Indeed, because so much of our learning is essentially unconscious, students new to self-reflective writing about learning often think that such writing is pointless. 

In fact, however, metacognitive awareness fostered by reflection can help students in a number of ways.  One, described in the preceding entry, is by making efforts to unlearn prior but misinformed learning; another is by helping students build better self-assessment skills.  Very few students enter the university with strong self-assessment skills, and the results of that can be confusion and diffidence when faced with new and more demanding grading standards. Developing a conscious understanding of one’s learning strengths allows one to direct attention to weaknesses even as it also promotes self-confidence in the skills one already has. 

Metacognitive reflection can also build resilience in the face of difficulty because it enables students to analyze better what in their efforts to learn something is causing confusion, and thus what needs more work and/or help.  Finally, by making students more consciously aware not just of the particular elements of their learning but also of their connections to other things they know, strong metacognitive habits can greatly help students develop their ability to transfer learning from one context to another (see the entry for Transfer below). 

*Self-assessment:  Self-assessment is the ability to assess one’s own performances accurately. Students very often bring weak self-assessment skills to any given class.  Gerald Graff (in Clueless in Academe: How Schooling Obscures the Life of the Mind [2004]) argues that academic experience is often highly mystified and mystifying for students, and nowhere more so than in how they are graded.  Many students have not been able to develop a good sense of what they do well and what they do not do well, and in the absence of a genuine understanding of their abilities they can become diffident and anxious, or (an even less helpful outcome) resistant to and alienated from the entire learning process.

When, by contrast, teachers help students learn to self-assess by sharing realistic criteria with students, much of this mystery can be removed, since students then have the means to assess for themselves how they have or have not succeeded. 

Motivation: terms often associated with motivation include: extrinsic, intrinsic; autonomy, competency, connectedness, punishments, rewards.

Motivations in learning are the thoughts, hopes,fears, pressures or needs that make one want to learn. How students can be motivated to learn has long been a major challenge in learning theory because, quite simply, many students in many classrooms often seem uninterested in learning. We human beings may be learners by nature, but our motives for learning “on demand” and particularly in school settings, have often proved difficult to develop and maintain. 

The most frequent analysis of motive talks of “intrinsic” vs. “extrinsic” factors. In this way of thinking, people act either for their own “intrinsic” (or internal to the self) reasons like self-respect or a sense of one's increased power or influence, or they are motivated by material rewards like money, awards, or high grades.  Of the two, extrinsic motivation is perhaps the best known, including as it does both positive rewards of various kinds, like money (prizes or increases in salary) and high grades, or negative rewards, like low grades, detentions after school, or extra homework.

Much of the conversation about motivation has concerned which extrinsic factors work best. Will workers be motivated better by cash or by a promotion? Are students best motivated by grades or... well, what extrinsic rewards DO schools have to offer? For most students a high grade is pretty much it.

In part as a result of the many weaknesses of extrinsic motivations, other research on motivation has focused on “intrinsic” factors. One of the best known theories of intrinsic motivation is Self Determination Theory (SDT). There we human beings are seen as complex beings with needs, fears, and hopes—needs that for many of us are often unconscious or unacknowledged but have great power in our minds and lives. SDT proposes that human beings are best motivated by three basic inner needs: autonomy, competency, and connectedness. Autonomy is the sense one can have of control over one’s own life and actions; Competency is the sense that one has power to do things of value, and Connectedness is a sense that one’s actions are serving or helping to build something that is socially meaningful.

For SDT advocates these inner motives are powerful, and success in school can do much to build and support students' self-respect. At the same time, their effects can also be difficult to measure: how does one connect a sense of autonomy or connectedness to the memorizing of new vocabulary or the studying of a list of state capitols?

*Self-Efficacy: This is a student’s inner level of confidence and capacity when facing a learning task. Unsurprisingly, self-efficacy varies a lot from student to student, but its effect on learning is significant. High levels of self-efficacy usually mean high levels of engagement and achievement because students with strong self-efficacy don’t let short term difficulty put them off learning. When students are used to thinking that they will be able to do something successfully they are also likely to have more willingness to problem-solve and push through to succeed than when they do not have that same confidence.

Contrariwise, when students have a low sense of self-efficacy, they may show less willingness to engage in a task at all.  Interestingly, students do not automatically have strong feelings of self-efficacy just because they have been successful as learners. Students with negative views of their self-efficacy may attribute success to luck or special conditions, not to their own problem-solving abilities.  Metacognitive reflection as well as demystified classroom practices can help students develop a more just and positive understanding of their self-efficacy, and thereby strengthen self-efficacy beliefs. 

*Resistance: Resistance to learning is anything a learner does to put off or avoid learning something and can be passive, active, conscious, or unconscious. Resistance is not just common among human beings, it is universal. None of us are always receptive to more and more learning. Moreover, some resistance needs to be cultivated as necessary to effective critical thinking. People are, after all, always trying to “teach” us things that are wrong or misleading. Being able to resist other people's theories is part of being a responsible critical thinker and citizen. 

But while resistance is often conscious (like the resistances Herb Kohl describes in “I Won’t Learn from You”), it is also very often passive and unacknowledged—even unconscious. To cope successfully with resistances students need to become able to recognize them, and must be given constructive ways of talking about them.

Resistance can be productive when it is active (and conscious), not passive or unconscious, and when a classroom environment supports students in voicing their reasons for resisting.  Similarly, teachers can help students by “authorizing resistance”—explicitly inviting them to locate and describe what they are resisting.  When a teacher creates a classroom atmosphere in which student resistance is authorized, students may be able to feel safe in talking about issues they would otherwise never raise. As a result, teacher can know better what and how a student might not be learning.

*Not-learning:  A form of resistance to learning in which someone attempts to prevent learning from happening altogether. Among students it may be a conscious strategy—as Herb Kohl describes in recounting the anecdotes of Wilfredo or Rick in “I Won’t Learn from You.” But not-learning is even more frequent in the world than Kohl suggests. Kohl’s focus is on conscious not-learning, a form of active resistance for either political or personal identity reasons. But the fact is that all of us not-learn regularly.  One reason for this is that there are so many things to pay attention to that no one could ever attend to them all. As a consequence, our unconscious minds are constantly doing a kind of epistemic triage, deciding what we will attend to, what we will doubt and what we won’t entertain at all.

Yet another reason students not-learn is that many of the things the world encourages us to learn go against what we already know or believe, and for most of these things we often turn down anything that would disturb our normal ways of seeing the world. Former Vice-President Al Gore talked of the facts of climate change as “inconvenient truths”—truths that would disturb how we think about the world and, more importantly, how we live our lives. His argument was that many of us are emotionally, economically or egocentrically unwilling to make the kinds of change that such inconvenient truths seem to demand, and thus we choose to not-learn either the science of climate change or its implications. “Temporary learning” (see next entry) is another common version of not-learning. 

Temporary, or pro-forma, learning:  A widespread phenomenon in academic learning where students learn things for a short period (sometimes only long enough to take an exam), but don’t actually learn them deeply and with retention.  Inauthentic learning (see “Authentic Learning” below) is very often of this sort.  When minds do not have strong motives for remembering something, the half-life of learning will often be correspondingly short.  (One classic study suggests that retention of learning from many lecture classes—not high to begin with—is among most students cut by half or more within 6 months.) 

Deep learning:  Something like the opposite of temporary learning is deep learning.  Education scholars use this phrase to mean learning that is highly motivated and fully (“deeply”) understood. Retention will be deepest and thus most robust when students have fully integrated the target learning into their own core understandings, and have been able to articulate it in their own language and in connection to other well-established understandings. Deep learning is something like the highest value of education since such learning is not just retained longer but is also a better basis for extension and transfer to new contexts than is less deeply understood learning. 

*Authentic (vs. inauthentic) learning:  Authenticity concerns a given student’s motivation for learning.  Authentic learning is that which makes a kind of deep sense to a student, seeming for whatever reason truly useful, or connected to a deeply felt life purpose (cf Motivation, [see entry above], and SDT). 

By contrast, the classic inauthentic motive for many an assignment and many students is a grade.  Some of us were deeply motivated by grades, but many students are not. They may want good grades, and they may work hard for them, but they often do not retain the learning that earned those high marks. Inauthentic learning is frequently a kind of going through the motions, though many students will smile, look engaged, seem perfectly happy. And they may even be engaged and happy, too.

The entire phenomenon of authenticity is complicated by the mysterious nature of “motive.”  Consider that while students may really like to listen to music and often “know” it inside and out, they might well not be able to articulate reasons why they are willing to learn its rhythms and lyrics so well, but their unconscious minds somehow decide to soak them all up. Many of us learn songs without studying their lyrics or their tunes, and yet we may keep them in mind for a lifetime. (I can sing advertising jingles I learned when I was 8 or 9 years old--and trust me, that was a long time ago!)

In school, by contrast, students might be quite happy in a given class, and even trying to learn, but their inner motivational disposition may nevertheless still not be strong enough to ensure remembering the course material beyond the end of the term. For students as well as their teachers, the great challenge is to figure out what will motivate learning in a deeper and more authentic way. 

Difficulty:  As learners, we all have different responses to the difficulties we run into.  Some of us look for it, seek it even; some of us hate it, can’t stand dealing with it.  Most of us probably have a complicated relation to difficulty—embracing it on one occasion, shying away from it on another.  Whatever one’s response, people tend to do best with difficulty when they have the metacognitive ability to recognize it, define it, and work to find a productive strategy for dealing with it. 

Failure:  We all are pretty sure we know what failure is, and it’s no surprise that we’d normally prefer success. We may be less likely, however, to see that many kinds of failure are actually healthy and necessary parts of learning. Indeed, in the case of complex processes, most learners will not be fully successful attempting them even after trying over and over again. (Just try to learn to juggle three balls at once without ever dropping one of those balls!) For those who have developed a fear of failing, or a propensity to avoid situations in which they imagine failure is possible, they similarly will have developed a type of learning disability as well.

Strong learners will learn that many tasks require persistence in the face of possible or actual failure. This is connected to the concept of “risk taking,” again something necessary to many kinds of learning.  Those who cannot take risks on occasion will be less effective learners than those who can. 

*Resilience:  “Resilience” is a term to describe a learner’s ability to be persistent and to keep working at a task in the face of difficulty and/or failure.  Research shows both that different learners evince different degrees of resilience when facing a certain task, and that students’ capacity for resilience can be increased, primarily by metacognitive exercises and by teacher’s or other students’ support as they encounter difficulty and its resultant frustrations in the course of learning challenging material. 

There is also research that shows that learners who believe hard work can make one "smarter" tend to be more resilient than those who believe intelligence is fixed. And indeed, there are many ways by which one can make oneself "smarter," and becoming more aware of your learning situation (i.e., becoming a more metacognitively informed learner) can be one way to do so.

*Transfer:  The act of taking something learned in one context and bringing it to bear in another, differently defined context.  Recent work has stressed the notion of “dynamic transfer,” noting that we don’t usually transfer knowledge directly from one problem to another in a single moment of insight, but by working at something over time, trying first one thing and then another until a solution begins to emerge.   One reason problem-based-learning (PBL) has become more wide-spread is its underlying claim that as one builds problem-solving skills one also builds the kinds of mental habits that promote transfer. In this way of thinking, the more success students have figuring out how to extend their knowledge to accomplish new tasks, the more extensive and resilient their general transfer abilities become.

Bridging the School-Life Gap:  I’m convinced that many students often keep the world of school learning at something of a distance from their real life learning. That doesn’t necessarily mean that they don’t like school, only that they see school learning as in at least some degree unreal or impractical. Students often do not themselves know how to bridge the gap from the subjects they care about in their own lives to the classroom subjects they care much less about. Teachers may actually encourage the maintaining of this gap when they don’t ensure that students bring their own enthusiasms and expert knowledges into a classroom. Teachers need to find ways to bridge the gap between what they are teaching and what students already know. For their part, students will benefit if they can learn (either on their own, but more frequently by being taught) to recognize the gap, and develop their own ways of bridging it, too. 

*Threshold Concepts:  “A threshold concept can be considered as akin to a portal, opening up a new and previously inaccessible way of thinking about something. It represents a transformed way of understanding, or interpreting, or viewing something without which the learner cannot progress. As a consequence of comprehending a threshold concept there may thus be a transformed internal view of subject matter, subject landscape, or even world view.” (Meyer and Land, “Threshold Concepts and Troublesome Knowledge” [2002],3)

That is from the inventers of the term; more completely, threshold concepts are those concepts or ideas in any given discipline that seem counterintuitive or even impossible to understand. Often they define ways of thinking that differentiate that discipline from other disciplines by seeing (or re-seeing) a phenomenon in ways that the uninitiated find inconceivable. 

Thus in biology the concept of evolution is central to all that biologists do, yet natural selection, a big part of how evolution is claimed to work, conflicts with a general human tendency to see actions as goal directed.  Thus for biologists fish (for example) did not evolve fins in order to swim in the sea, or in order to supply food to you and me, or for any other purpose.  Rather, they evolved fins by a random process of genetic mutations, one of which happened to produce fin-like organs, and thereby provided a reproductive advantage. The point is that a key part of biological change is random, not purposeful, and if you don’t see what that means, you won’t “get” biology at all.  

Economics deals with the costs of things, of course. But they talk not just about "cost" but about "opportunity cost" as well, a threshold concept that asks us to think counterintuitively of “cost” not in terms of price but in terms of what the acquisition of something would prevent our being able to do with the resources used for the acquisition.  Price alone, or even how much money you have in your pocket, an economist might say, is not knowledge enough to evaluate whether or not you have made a good buy. 

Zone of Proximal Development (aka, ZPD): The ZPD is a term Lev Vygotsky introduced to identify the situation within which optimal learning can occur. In his words it is: "the distance between the actual developmental level as determined by [a student's] independent problem solving and the level of potential development as determined through problem solving under adult guidance, or in collaboration with more capable peers" (Vygotsky, 1978, p. 86)

That's a little complicated, but it's still worth figuring out. Applied to college classrooms the term ZPD defines the most appropriate level of difficulty one can provide to one's students. What a good teacher will want to do is estimate carefully abilities of incoming students and then, based upon that estimate, make a second estimate as to how much progress students in the class will be able to make within the time a given course can provide.

If a teacher pitches material below that zone, students will become bored for lack of challenge; if a teacher pitches material above that zone students will find the course too difficult and may grow frustrated and bored because unable to succeed. In the perfect case a teacher will have predicted accurately both where along the axis of difficulty incoming students will be and how much progress students can effectively make.

All of this is a way of cautioning teachers that the best planned classes are those that start with accurate estimates of student-incomes and progress within a zone of possible development that is reasonable and rewarding. Some will say that reaching that goal requires special attention to the level of expertise students bring to the class. Indeed, one worthy premise for any teacher and any class is "Teach the students you have, not the students you would like to have, or the student you once were."

For students, by contrast, the challenge is to learn how to recognize a class which has set the incoming level of difficulty either too high or too low. If the difficulty is too high, students need to be ready to seek additional help; if it is too low, they should think either about taking something more challenging or talking with the professor about more advanced issues.

*Cognitive Biases Among the greatest of challenges to thinking well are cognitive biases. These are tendencies our unconscious minds have to prefer one way of thinking over another without having convincing evidence to support that preference. One such bias is the Confirmation Bias—the tendency that all of us have to see new evidence as confirming a belief we already hold even when it may not be true. Though we are usually unconscious of it, most of us tend to value what we already believe over new information, and thus most of us can be quick to ignore or deny anything that might change our minds.

The idea that we have biases built into our brains sounds a little crazy, but it does make sense. In order to think rapidly—especially in an emergency—our brains have developed a set of automatic and time-saving shortcuts. In the face of a charging elephant, after all, you don’t have much time to think! Over the course of human evolution it has often been more important to be able to make quick decisions than correct decisions, and so that’s what our brains have evolved to do.

The defense we have against such biases is first to be aware that they exist, and then, second, to make it a habit to keep asking oneself whether a confirmation bias (or any other bias—there are actually quite a few of them) is affecting the thinking or learning one is attempting to do at any one time.

Other cognitive biases include the Halo Effect (Someone famous says something and we tend to believe it just because we admire famous people), the Anchor Effect (the “tendency to rely too heavily on the very first piece of information” you learn in a sequence of pieces of information), and the Availability Effect (the way we place greater value on the information in our memories that comes to our minds quickly—and is therefore more “available”—than information that takes time and effort to recall or research).

For further explanation see https://www.verywellmind.com/what-is-a-cognitive-bias-2794963. There is also a long and growing list of biases at:

https://en.wikipedia.org/wiki/List_of_cognitive_biases

 

Suggestions for Further Reading: There are many books dealing with issues of learning, and many are written for general audiences. Annotated descriptions of a number of such books can be found at:

http://faculty.washington.edu/cicero/learningresources.htm

John Webster©2021