Dave's Whiteboard

Yes, you’re right.  Head First Statistics is really a form of teaching, not learning.  As with any book, you could see it as an extended lecture (660 pages, if you count the appendices).  No way to ask anything, easy to slide past questions or problems by turning the page.

Which is why HFS makes such a great example of a tool (depending on your interests) and such a great example of fun (depending on your mindset).

Those two “depending on” clauses are like the uprights for a suspension bridge.  If you’re not interested in learning about statistics and nothing’s pushing you to do so (like your job or your graduate program), then I’m confident (at the 0.975 level) you’re not going to, regardless of the form in which the opportunity to learn appears.  Much the same is true for the other upright: the way you feel about this particular opportunity. 

HFS has given both ends of that bridge some thought. Click the sample page to enlarge; you’ll see what I mean.

♦  ♦  ♦

What Dawn Griffiths has done is sketch a very high-level picture of the learning goals that HFS supports and the types of people who probably respond well to this approach.  Who’da thunk you could do that without the sacred incantation, “At the end of this course the student will be able to…?”

But–how can you be sure of what you’ll learn?

Hmm… the body-of-knowledge approach to learning.  It’s true: in many fields like statistics, there are concepts, principles, terms, equations, and so on that you’re expected to know.

By “know,” I mean you can agree on a description or definition for X with people who aren’t related to you.  Even if their reaction is, “Well, you could put it that way.”

At the same time, despite the sputterosity of purists, zealots, and cranks with time on their hands, most fields don’t have a body of knowledge; they’ve got a herd. Beyond the most basic definitions (like the difference between mean, mode, and media), no one factoid is make-or-break.

Granted, statistics does tend toward the lots-of-specific facts side. So HFS furnishes some tables.

A “Table of Contents (Summary),” which takes up a little more than half a page.  It’s followed by “Table of Contents (the real thing)” with a page for each of the 15 chapters, plus half a page apiece for the intro appendices).  Check the O’Reilly Books preview page for HFS yourself; use the next / previous buttons at the top of the book page to browse.

If I were smart, I’d end by suggesting you also look at a sample chapter (probability, PDF) or explore HFS on your own via Google Books.  The good-humored approach, the absence of dense text–those are obvious at first glance.

Beneath that, though, there’s a lot of cognitive infrastructure, the sort of thing that shifts from “fun” to “learning.”  Chapter 3, “Power Ranges,” is a good example.  It’s got 44 pages dealing with range and variation (the previous chapter dealt with mean, median, and mode).  This is what’s lurking as you turn the title page:

• The coach of the neighborhood basketball team needs one player.  He’s got three candidates.  All three have the same shooting average.  So, which one should he pick?
• Here are their individual stats (points per game and frequency).  What else does the coach need to know?
• Explanation: what “range” means (also, lower bound and upper bound).
• You try it: figure the mean, lower bound, upper bound, and rang for these two players.  Then, draw a histogram (as you learned in chapter 2) for each.
• Feedback for that exercise, and a troubling question about outliers.
• Explanation: why outliers are problematic.  Can you think of how to reduce their impact?
• Explanation: why ranges are quick-and-dirty solutions.
• Sneaky intro (“one way is to measure only part of the range”)
  accompanied by this:

That’s the first 8 pages.  Not only did you have a couple of get-out-your-pencil problems, but also questions to provoke thinking, questions to highlight potential confusion, and even, as in the above example, questions that are intelligent stand-ins for ones a learner might have.

As I said in an earlier post, fun in training (or in support of learning) shouldn’t be an afterthought.  It shouldn’t be force-injected, either, like the fake smoke-flavored streaks applied to frozen burgers to make you think they were grilled.

Dawn Griffiths shows that part of the engagement comes from a general approach (irreverence, retro photos, quirks of layout); another part comes from sample problems that offer real statistical challenges placed in…let’s say surreal settings.  (In chapter 7, you use Poisson distributions to figure out how often a movie theater’s popcorn machine is going to break downnext week.)

Maybe we can get Griffiths and the folks from Head First to have a long lunch with von Merriënboer and Kirschner.

Daniel Levitin used to be a record producer and a professional musician.  His fascination with how we grasp music, emotionally and physically, led to a new career as a professor of psychology and neuroscience at McGill University.  He’s followed an earlier book, This is Your Brain on Music, with The World in Six Songs.

I’m not far into it, but it’s already a “hey, listen to this” experience.  (Want to see the first chapter?)

Levitin contends that music isn’t simply a distraction or a pastime, but “a core element of our identity as a species, an activity that paved the way for more complex behaviors such as language…”

The six songs of the title aren’t specific songs; they’re categories for how we fit music into our lives.  At the start, he says, he was trying to figure out what all the different forms of song–work songs, love songs, counting rhymes, nearly the entire work of Bobby McFerrin–had in common.

Anthropologist Jim Ferguson (no relation that I’m aware of) told Levitin that was the wrong question.

Quoting the great anthropologist Clifford Geertz, Jim persuaded me that the right question to ask, in trying to understand music’s universality, is not what all musics have in common, but how they differ….

it is in the particulars, the nuances, the overwhelming variety of ways we express ourselves that one can come to understand best what it means to be a musical human.

Levitin sees six types of songs as having shaped human nature: songs of friendship, joy, comfort, knowledge, religion, and love.  Interestingly to me, his definition of “song” is “any music that people make, with or without melody, with or without lyrics.”

I like the inherent complexity (and possible paradox) in that.  “Without lyrics,” for example, opens the door for the effect that deliberate rhythm may have had on human behavior and the evolution of the brain.

I also like insights he includes from Pete Seeger.  Pete pointed out that not all music is intended to be popular.

“Among American Indians,” Seeger explained, “a young man got his eye on a girl and he would make a reed flute and compose a melody.  And when she came down to get a pail of water at the brook, he would hide in the weeds and play her his turn… It was her special tune.  A tune wasn’t thought of as being free for everybody.  It belonged to one person.  You might sing somebody’s song after they’re dead to recall them, but each person had a private song…”

In addition, Seeger says, the power of music comes from its combination of form, structure, and meaning.  “Ordinary speech doesn’t have quite that much organization….and this becomes intriguing, something you can remember.”

Levitin suggests that before there was language, the human brain didn’t have the full capacity to learn langauge.  That capacity emerged as the brain worked with sounds and verbalizations.  The new structure, he says, made possible three cognitive abilities:

• Perspective-taking: we could think about our own thoughts, and could realize that others have thoughts different from our own.
• Representation: we could think and talk about things that aren’t present.
• Rearrangement: we can “combine, recombine, and impose hierarchical order” on things in the world around us.

I’ve got a number of music- or language-related thoughts circulating.  This post is the first verse.

Stephen Downes recently posted a detailed essay on “21st century skills,” An Operating System for the Mind. He’s asking whether and why a common core of knowledge is necessary, and whether students ought to be tested on that core.

Downes is thorough–copied into Word, the post comes to eight single-spaced pages. I wanted to read it and follow what he’s saying, which explains this post. If things aren’t clear here, blame me.  Then, read Stephen’s original for yourself.

The bottom line: while factual knowledge is helpful, certain key skills are essential; they are a kind of operating system for the mind, which can then work with data from the outside world.

What’s at the core?

By “core knowledge,” he’s talking about a body or collection of things that provide the basics in a given field (e.g., you “need to know about bones to study medicine”).  He’s not saying you can’t teach (or learn) facts; learning facts is “the great shortcut in human development.”  And in order to do anything, you need to know stuff.

The question is, why these specific facts? In other words, is there a common core?

Downes says that facts learned as facts (like the multiplication tables) are a kind of direct programming, the sort of thing that remains unquestioned.  And, frankly, facts aren’t enough.

It’s not just the facts, ma’am

Here’s my summary of his six main reasons that an education based strictly and solely on facts is insufficient:

• Too many facts: you can’t learn them all, so you have to know how to find them.
• Facts aren’t fixed: things change, and we need to learn, to “change the previously existing state of our knowledge.”
• Some facts matter more: we have to select and filter so that we can decide what facts are important to ourselves and to others.
• Calling something a fact doesn’t make it one: we need to compare and assess things presented as facts.  (For example, I have no interest whatsoever in any “facts” proving that the earth is less than 10,000 years old.)
• Some facts invite acts: we need skills to decide whether the facts we have are something we should act on, and the sense that we can by acting create new facts.
• Facts aren’t capabilities: Beyond seeing the possibility of acting, we need the ability to act.

The flip side of these insufficiences, for Downes, becomes a summary of so-called 21st-century skills.  I like that there’s nothing about multi-tasking or hardware infrastructure or evolutionary changes to the brain in them.  They’re stated in more general terms, and could have applied a century ago.

So what’s different?

President Kennedy said at a 1962 dinner for Nobel laureates:

I think this is the most extraordinary collection of talent, of human knowledge, that has ever been gathered together at the White House, with the possible exception of when Thomas Jefferson dined alone.

But that was 47 years ago, and 28 years before the world’s first web server.  We’ve got more facts and less static facts all the time.  (Remember how science “knew” that stomach ulcers were caused by stress?)  Beyond knowing what’s new and what’s changed, we have to cast a wider net.  Here Comes Everybody is not just a book title–it’s a new form of input.

Downes argues we also have new types of knowledge and skill, and that more of us need to use them every day.  (Baby Boomers are sometimes uneasy when they read “email is for old people.”)

Consider also the skills needed to manage just your professional presence and reputation.  That used to be done almost exclusively on paper and in person.  Now you’ve got networking sites, blogs, personal domains, avatars… your “online self” is a sort of conceptual clown car, with all sorts of characters inside.  Good thing we have so many more ways to do that.

Downes says, in part, that the role of facts is decreasing as the need for dynamic skill increases:

People need such greater capacities in literacy, learning, prioritizing, evaluation, planning and acting.

Facts: they don’t compute

Downes has an extended, useful comparison between these skills and the way we use computers.  To vastly oversimplify, other than its operating system, a computer doesn’t know anything.  (I tend to say it’s dumb as a rock but fast as hell.)  “If we had…programmed into [the computer] the knowledge of finances, literature, and mathematics, it would have been a less useful computer.”

That’s why, when we design computers, first we build the hardware, then we install the operating system, then we install application programs, and only then do we add the data – the facts with which we expect our computer to work.

The same principle applies in education and learning.

Take driving, for example. If our knowledge of how to drive depended on a set of facts, then at a certain point it would become impossible, because while we could teach people how to drive on common streets and in common situations, as we drive further and further away from home, in newer and different vehicles, our knowledge becomes less relevant, until eventually we are simply unable to drive. If, instead of focusing on the ‘facts’ of driving, we think of driving as an activity or skill, then we are able to adapt, and develop new abilities, and new knowledge, mastering the ability to drive in strange places as we progress.

…which is why Downes sees 21st-century skills as an operating system for the mind.

What the new operating system does

These skills enable us to navigate, to see, to understand, and to make our own decisions.  More important, says Downes, they change how we see facts.

To me, this is like the old view of the atom as an indivisible particle.  A fact is a thing, it’s true, it’s “real.”  Downes argues that “our relation with facts is much more contingent than previously supposed.”  (His italics.)

• Facts are not independent of how they’re expressed. Literacy means reading the lines, and between the lines, but also “reading faces, photos, ideas, omens, and portents.”
• Facts change. That’s a fact.  The earth isn’t the center of the universe.  Solid rock isn’t solid.

nobody
belongs anywhere
even the
Rocky Mountains
are still
moving
— George Bowering

• Some facts are salient, some aren’t. There’s no one set of facts that’s important to everyone.
• You can learn to tell fact from non-fact. Detecting deception (or, I think, error, or misrepresentation) is a skill, Downes says, “and you need just as much as your computer needs to be able to detect malware.”
• You’ve gotta decide. This point is key: decision-making isn’t rote performance, which means it’s not based solely on facts.
• You need to act. That action depends on skill much more than on a big ol’ heap of fact.

To be a man is to be responsible: to be ashamed of miseries you did not cause; to be proud of your comrades’ victories; to be aware, when setting one stone, that you are building a world.

—Antoine de Saint-Exupéry

I’m skillful enough to let Downes finish for himself:

We still to a great degree treat facts as things and education as the acquisition of those things. But more and more, as our work, homes and lives become increasingly complex, we see this understanding becoming not only increasingly obsolete, but increasingly an impediment.

Today…if you simply follow the rules, do what you’re told, do your job and stay out of trouble, you will be led to ruin. It’s like sitting on a log floating in a river: it works for a while, and seems like the safest place to me, but all the while, you’re approaching a waterfall. Whether it be a financial crash, the degradation of the environment, war and terrorism, or even something as simple as a car accident or family crisis, you will need more and more the ability to keep yourself afloat in troubled and rapidly changing circumstances, and an abundance of facts will not help you, it will instead sweep you over the waterfall.

CC-licensed images:
Rolodex cards by mrbill;
facets of faces by Axel Bührmann.

I collect rules-of-thumb the way some people collect fantasy sports-league players.  (Willy Pareto? Economist out of Turino Tech.)  But I’m cautious when the rule seems too broad or the numbers too specific.  After all, it wasn’t Vilfredo himself but Joseph Juran who suggested that the 80/20 rule be called the Pareto principle.

Lately I’ve been trying to change some everyday behavior, and so this PsyBlog post, How Long to Form a Habit?, pulled me in.

(Disclaimer: when someone asks, from a training viewpoint, “How long does it take to develop [whatever]?” I habitually ask myself, “How long is a rope?”)

The PsyBlog post says participants in a study (working on new habits like eating fruit with lunch or running 15 minutes per day) on average hit a plateau in about 66 days.  As the chart (from the post) shows, you get to your “drink more water” goal much fasts than your “do 50 sit-ups” goal.

The post links to an abstract for the actual study, which notes that of the original 96 participants, 82 had enough data for the study, 62 fit the statistical model, and 39 had “a good fit.”    And the range to automaticity varied–from 18 to 254 days.

I got curious and found some other items on habit, which Wikipedia defines as a routine of behavior, repeated regularly, that tends to occur subconsciously.

Under that definition,  I have a habit of carrying my wallet in my left front pocket; this is an oddity, I realize, but it’s behavior of longstanding, such that I feel strange to have the wallet anywhere else.

Habits are learned behaviors, and a 2005 article on CNET News cites an MIT study looking at how old (presumably bad) habits reassert themselves.  It claims habit gets established in the basal ganglia (site of, among other things, procedural learning and addictive behavior).

Backsliding is easier, then, and to counteract it, we may need to be conscious not only of the former habit but of the presumably better behavior we want to make as automatic as possible.

I found lots of silliness–21 days to establish a habit, or 99, or 60, and one guy who said he could establish one in a day.  (Maybe if you’re establishing the habit of having maple syrup on vanilla ice cream.)

If it’s not currently part of your standard behavior, then to establish a habit, you’re got to exert some effort.  Initially you’re likely dealing with a lack of immediate, enjoyable payback.  And almost by definition, you’re disturbing of your behavioral routine.

I found a 2007 Psychological Review article by Wendy Wood and David T. Neil, A New Look at Habits and the Habit-Goal Interface (21-page PDF).

Habits are learned dispositions to repeat past responses. They are triggered by features of the context that have covaried frequently with past performance, including performance locations, preceding actions in a sequence, and particular people. Contexts activate habitual responses directly, without the mediation of goal states.

In other words, acquiring a habit means you’re likely to repeat a given action.  Settings that invite that action do so directly–you don’t think about losing weight (a goal) as you do about eating fruit rather than a bag of chips.

Wood and Neil propose three principles:

• Habits are cued by context. You can learn to associate a context; after a while, the context can do its own triggering.  (This explains the advice to insomniacs about not watching TV, reading too much, or tossing and turning for long times in bed.  They’re working to create an association between bed and sleep.)
• Over time, the goal fades but the habit remains. ( “Habit context-response associations are not mediated by goals.” )This explains why my dad continued to buy kid-friendly cereal years after all of us were grown and married.  He’d done the grocery shopping for 20 years; his choices were a habit.  He didn’t eat the cereal himself, and my mother’s…feedback, let’s call it…took a long time to have any impact.
• Habits interact with goals. Initially, goals direct habits; over time, habits and goals influence each other.

It seems to me, then, that when we talk about acquiring good habits, we’re likely not only adding to our current repertory of activity; we’re likely replacing something seen as less helpful.

The Wood & Neal article discusses that at more length than I have space in this post.  Also, I haven’t fully established the habit of reading 21-page journal articles on the screen.  So I’m printing the PDF, and I’ll have a future post on habits, goals, and how they might get me to the gym more often while surfing online a bit less.

I’ve already mentioned David Sousa’s How the Brain Learns, but I keep going through it and thought it deserved a little more exposure.

Sousa’s writing for teachers (including college and university faculty), along with principals and staff development folks. Almost everything here offers value for the corporate trainer or instructional designer, in terms of more structured learning

A lot of makes sense for less formal learning as well.

It’s clear from the outset that Sousa does what he encourages you to do.  By the time you get to page 9 (there are 300 pages), he’s nudging you to do more than just read:

One of the best ways to assess the value of the strategies suggested in this book is to try them out in your own classroom or in any other location where you are teaching. conducting this action research allows you to:

• Gather data to determine the effectiveness of new strategies and affirm those you already use,
• Acclaim and enhance the use of research in our profession, and
• Further your own professional development.

Besides which, he says, you get feedback on how you’re doing (as an instructor or designer), and you can collaborate with your peers to apply the research more broadly or more deeply.

So, what’s he offering?  The chapter titles are clear:

1. Basic Brain Facts (parts, development)
2. How the Brain Processes Information (models and their limitations)
3. Memory, Retention, and Learning
4. The Power of Transfer (both transfer during learning and transfer after learning)
5. Brain Specialization and Learning (lateralization, spoken language, learning to read)
6. The Brain and the Arts
7. Thinking Skills and Learning
8. Planning for Today and Tomorrow

Each chapter includes a section called Practitioner’s Corner. These are short, focused sections to help the teacher (trainer, learning professional) move stuff off the pages and into her repertory of skills.  For chapter 3 (memory, learning, retention) there are ten practitioner’s corner items.  They range from “avoid teaching two very similar motor skills” to “strategies for block scheduling” to “using rehearsal to enhance retention.”

I’ve actually felt a little intimidated by How the Brain Learns. I look at what Sousa’s done and think “I ought to be doing my own action research.”  I ought to create and document not only some successes from what I’ve done–but make those potential resources for future clients and coworkers.

• What am I trying to do?  What’s telling me to try it?
• What difference will it make?  How can I tell?
• What difference did it make?
• What do I do now?  What can I do better?  What’s telling me that?