Have you ever considered how vulnerable students are to teachers, both to teachers' criticisms and to teachers' false beliefs? Considering how vulnerable students really are, is it any wonder some of them shut off in school? So what's the answer? Forcing kids to listen? Forcing teachers to make sure kids never feel forced to listen? This week, in our ongoing series on education and learning, we're going to take a look at something I call the "Cycle of Teachability." In it, we'll begin to see what makes kids in classrooms tick. And adults in classrooms as well. 
Chapter Fourteen "From Naive to Arrogant and so on ..." 
Have you ever felt in hindsight you were naive, because you believed something a teacher said which later turned out to be untrue? Have you ever had this naive feeling then evolve into the more self critical version of hindsight, this being the feeling that you were stupid for ever trusting this teacher? I've felt both in my life time. Probably more the later than the former. Perhaps this is why I tend to lean toward the skeptical side of the Teachability Index rather than toward the trusting side. Self preservation? Probably. I do need to believe I am not completely naive. Can you imagine how this fear has affected my teachability over my life? As well as my abilities as a teacher? In truth, my openness to teachers has cycled through a lot of changes. And because I believe myself to have cycled through one of the two main teachability patterns, I'm now going to give you the ten cent tour. Please bear with me.

the Two Teachability Cycles 
If you now take a look at this week's diagram, in the upper half, you'll find my whole journey mapped out. Know this is but one of three possibilities. The first possibility, the upper cycle, is the Born Open Cycle. This is the path I followed over the course of my life. It is also one of the two possible teachability paths taken by babies who arrive in a house wherein their parents are either two open or two closed to teachers. In the lower half is the second possible path, the one taken by folks who start life closed to teachers. I call this, the Born Closed Cycle. These folks seem to have been born arrogant. Imagine? Babies born closed to teachers! This path, then, is the second of two possible paths taken by babies who arrive in a house wherein their parents are either too open or too closed to teachers. In between these two cycles, then, is a starting place wherein babies do not really have big swings over the course of their lives. These babies seem to have been lucky enough to have been born into a family wherein their parents love learning. Thus, these babies seem to have been born ready to learn. And they were. Now for those who are familiar with the work of theorist John Bowlby (attachment theory) , know these three teachability cycles very much parallel his work in and around how babies attach to primary care givers. Thus, he says babies, at birth, arrive with one of three possible reactions to others programmed into their personalities; [1] warm, [2] slow to warm, and [3] cool. I see his three states as being the three possible ways in which we arrive already programmed to react to teachers. Interestingly enough, regardless of which end of the teachability index we start on, growing older seems to provoke a lot of change in us, including that we are generally programmed to become more teachable the older we get. Even the lucky, slow to warm babies. Of course, even knowing how someone is programmed does not guarantee you can predict to what point this growth will occur. Only that to some degree, it will happen. And that people will feel urges to switch directions at times in their lives. In a way, what I'm saying is, most children begin school either arrogantly closed to teachers or naively open to teachers. And if you remember the bell shaped teachability curve from a few weeks back, you'll remember that people at either of these two extremes learn very little. Which is why so few kids end up excelling in school. And why cycling between these two points as we grow older tends to round off some of our educational "sharp edges." Which, in general, means we get more open to learning the older we get. My point? Healthy people get better at learning the older they get. Some of us, me included, even reach the point wherein we fall in love with the idea of being either a student, or teacher, or both. And some of us seem to withdraw more and more each year from the joys of learning, as we more and more feel the need to protect ourselves from the pain of being seen as stupid. Or the aloneness of being arrogant. 
Using Hallmark Cards to Teach Love 
Okay. So what good does it do us to know these two cycles exist? Any good at all? In reality, it does us a lot of good. How? Well, let's consider for a moment my angry stand against statistics a few weeks back. Wasn't this me being arrogant? Or at the very least, cynical? In truth? How about if I let you judge this for yourself. I have a beef with statistics. Yes. I admit it. Moreover, I have an even stronger beef with people who hawk psychological statistics like the scientific end all be all against which case studies have no weight. Please know, my beef is not that these folks try to understand people better. I agree with this goal. Rather, it is with the cold way in which they discount personal studies as the way to understand people. Their main complaint? They claim that "one person" cannot possibly be a big enough sample to learn from. In effect, that only with big sample sizes can ideas about people be considered true. Is this true though? Or can we learn about human nature from personally knowing only a few people? Or from knowing even one person? Before you answer, consider this. How many cumulus clouds do you need to learn to recognize in order to know how to recognize cumulus clouds. Ten? Five? Three perhaps. Now consider if your learning to recognize cumulus clouds was to depend entirely on statistical data; on huge numbers of numbers. What I mean is, imagine if you were told that, in order for you to trust your ability to identify cumulus clouds, you need to have sampled a statistically significant number of clouds. What then? Would you trust your judgment? What if the statisticians also told you that cumulus clouds account for 87% of all clouds. Would this help you to feel confident in your ability to recognize cumulus clouds? Would it confuse you more? Finally, what if you really needed to know how to identify cumulus clouds, because you were the person on whom people having picnics depended? Would you really want to depend solely on statistics to predict rain? In effect, be a living version of the Farmer's Almanac? In truth, while we often pretend that statistics are real, in reality, we base everything we learn for real on only two things, both of which can be boiled down to a kind of geometry. One, we learn things based on recognizable shapes which always repeat identically, like the squares and triangles of classical geometry. And two, we learn things based on recognizable shapes which always repeat differently, such as the cumulus clouds and oak leaves of fractal geometry. And statistics? Well, using statistics to learn things is like using Hallmark cards to learn about love. Yes, there's some vague resemblance to the real deal there, but no where near enough to be of any actual use. Now let me ask you. Do I sound arrogant now? Naive? Cynical? Or is there some thread of truth peaking out from beneath our blind trust in statistical numbers? Think I'm exaggerating? If so, consider this. Of the two most commonly respected current theories of personality, one is based almost entirely on statistics. This theory? Trait theory. Which is truly the epitome of Hallmark Card personality theories. It boils all of personality down to only five pairs of words. Imagine? Picking your future spouse based entirely on how she fairs with regard to only five pairs of English language adjectives! Emergence Personality theory uses no statistics and yet can recognize in excess of 384 personality types even at it's most basic level. How? By using personality fractals to identify the living, breathing, humanness in all of us. As for our topic at hand, what kills the love of learning, hopefully the teachability measuring stick I've given you (the Teachability Index) will offer you yet one more way to know people better. Including me and where I have been during this week's column. Obviously, I have been my usual, skeptical self. And just in case you see being skeptical as something pejorative, consider this. Most of the world's great philosophers are considered to have been skeptics. Socrates. Plato. Carneades. Kant. Descartes. Berkeley. Locke. Hume. Skeptics, one and all. Finally, just to be sure you haven't missed the primary point I've been trying to make, about how learning happens, please allow me to repeat these ideas about learning one more time. All real learning is rooted in becoming able to recognize a geometric shape. Moreover, there are only two kinds of geometric shapes; classical and fractal. What's the difference? Classically Geometric shapes (like cubes, rhomboids, spheres, and such) are "recognizable shapes which always repeat identically." These studies include all linear theory, such as linear mathematics (like algebra and geometry), linear physics (like vectors and Newtonian laws), linear sciences (like theoretical chemistry and genetics), and linear interpersonal studies (like law, logistics, and government ethics in the abstract sense). Fractally Geometric shapes, on the other hand, (which includes things like clouds, trees, rivers, and ferns), are "recognizable shapes which always repeat differently." These studies includes everything non linear, such as non linear mathematics (like irrational numbers and calculus), non linear physics (like quantum theory and general relativity), non linear sciences (like weather prediction and population growth estimates), and non linear interpersonal studies (like human psychology, gender studies, film critique, and creative writing). And statistics? Most statistics are more like groups of numbers which humans use to pretend they can predict things. This is why statisticians spend so much time trying to force fit their ideas into pie charts and such, in efforts to make these numbers resemble either Classically Geometric shapes or Fractally Geometric shapes. Rarely does this work, of course, which is why statistics fail to predict so much of what we use them for. Ironically, though, there is actually one fractal shape in statistics which is real and never fails. Which means that the statistics based on this shape are truly meaningful and genuinely useful. The fractal shape? The "Bell Shaped Curve." But then, you knew this already, now didn't you. Do I sound teachable now? 
Closing Comments 
Sorry if you feel I tricked you. I honestly didn't mean to make you feel foolish. Really, I didn't. On the other hand, if you do now feel anything between stupid and arrogant, please use this moment to remember what it feels like to have been tricked by a teacher. And remember to use this method wisely, and sparingly. I also hope you're beginning to see what makes me so dislike it when kids are judged by grades. It's not that I believe we should not hold kids accountable. Rather, I wish we had some grading method based on fractals. Imagine what a wonderful world that would create. Until next week then. I hope you're all well, P. S. And for those still wishing to see what they may learn, here's a link to the Teachability Index Worksheet. 
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