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CHANGE OF
PLAN: When I wrote last month’s post, I said I would conclude the
description of my Nueva School Course this time. But when I sat down to write up that
concluding piece, I realized it would require not one but two further posts.
The course itself was the third iteration of an experiment I had tried out on a
university class of non-science majors and an Adult Education class. This series
of articles is my first attempt to try to describe it and articulate the
thinking behind it. As is often the case, when you try to describe something
new (at least it was new to me), you realize how much background experience and
unrecognized tacit knowledge you have drawn upon. In this post, I’ll try to
capture those contextual issues. Next month I’ll get back to the course itself.
We all
know that mathematics is not always easy. It requires practice,
discipline and patience, as do many other things in life. And if learning math is not
easy, it follows that teaching math is not easy either. But it
can help both learner and teacher if they know what the end result is supposed
to be.
In my
experience, many learners and teachers don’t know that. In both cases, the
reason they don’t know it is that no one has bothered to tell them. There is a
general but unstated assumption that everyone knows why the teaching and
learning of mathematics is obligatory in every education system in the world.
But do they really?
There are
two (very different) reasons for teaching and learning mathematics.
One
reason is that it is a way of thinking that our species has developed over
several thousand years, that provides wonderful exercise for the mind, and
yields both challenging intellectual pleasure and rewarding aesthetic beauty to
many who can find their way sufficiently far into it. In that respect, it is like music, drama,
painting, philosophy, natural sciences, and many other intellectual human
activities. This is a perfectly valid reason to provide everyone with an
opportunity to sample it, and make it possible for those who like what they see
to pursue it as far as they desire. What it is not, is a valid reason for
making learning math obligatory throughout elementary, middle, and high school
education.
The
argument behind math’s obligatory status in education is that it is useful;
more precisely, it is useful in the practical, everyday world. This is the view
of mathematics I am adopting in the short series of “Devlin’s Angle” essays of
which this is the third. (There will be one more next month. See episode 1 here and
episode 2 here.)
Indeed, mathematics is useful in the everyday practical world. In fact, we live in an age where mathematics is more relevant to our lives than at any previous time in human history.
It is, then, perfectly valid to say that we force each generation of school students to
learn math because it is a useful skill in today’s world. True, there are
plenty of people who do just fine without having that skill, but they can do so
only because there are enough other people around who do have it.
But let’s
take that argument a step further. How do you teach mathematics so that it prepares
young people to use it in the world? Clearly, you start by looking at the way
people currently use math in the world, and figure out how best to get the next
generation to that point. (Accepting that by the time those students finish
school, the world’s demands may have moved on a bit, so those new graduates may
have a bit of catch up and adjustment to make.)
If the
way the professionals use math in the world changes, then the way we teach it
should change as well. Don’t you think? That’s
certainly what has happened in the past.
For
instance, in the ninth century, the Arabic-Persian speaking traders around
Baghdad developed a new, and in many instances more efficient, way to do
arithmetic calculations at scale, by using logical reasoning rather than
arithmetic. Their new system, which quickly became known as al-jabr
after one of the techniques they developed to solve equations, soon found its
way into their math teaching.
When
Hindu-Arabic arithmetic was introduced into Europe in the thirteenth century,
the school systems fairly quickly adopted it into their arithmetic teaching as
well. (It took a few decades, but knowledge moved no faster than the pace of a
packhorse back then. I tell the story of that particular mathematics-led
revolution in my 2011 book The Man of Numbers.)
The
development of modern methods of accounting and the introduction of financial
systems such as banks and insurance companies, which started in Italy around
the same time, also led to new techniques being incorporated into the
mathematical education of the next generation.
Later,
when the sixteenth century French mathematician François
Viète introduced symbolic algebra, it too became part of the educational canon.
In each case, those advances in mathematics were introduced
to make mathematics more easy to use and to increase its application. There was
never any question of “What is this good for?” People eagerly grabbed hold of
each new development and made everyday use of it as soon as it became
available.
The rise of modern science (starting with Galileo in the seventeenth century) and later
the Industrial Revolution in the nineteenth century, led to still more impetus
to develop new mathematical concepts and techniques, though some of those
developments were geared more toward particular groups of professionals.
(Calculus, for example.)
To make
it possible for an average student or worker to make use of each new
mathematical concept or technique, sets of formal calculating rules (algorithmic
procedures) were developed and refined. Once mastered, these made it
possible to make use of the new mathematics to handle—in a practical way—the
tasks and problems of the everyday world for which those concepts and
techniques had been developed to deal with in the first place.
As a
result of all those advances, by the time the Baby Boomers came onto the
educational scene in the 1950s, the curriculum of mathematical algorithms that
were genuinely important in everyday life was fairly large. It was no longer
possible for a student to understand all the underlying mathematical concepts
and techniques behind the algorithms and procedures they had to learn. The best
that they could do was master, by repetitive practice, the algorithmic
procedures as quickly as possible and move on. [A few of us had difficulty
doing that. We wanted to understand what was going on. By and large, we
frustrated our teachers, who seemed to think we were simply troublesome slow
learners. Some of us eventually learned to “play the mindless algorithm game” in
class to pass the test, but kept struggling on our own to understand what was
going on, setting us on a path to becoming mathematics professors in the
1970s.]
It was
while that Boomer generation was going through the school system that
mathematics underwent the first step of a seismic shift that within a half of a
century would completely revolutionize the way mathematics was done. Not the
pure mathematics practiced by a few specialists as an art—though that too would
be impacted by the revolution to some extent. Rather, it was mathematics-as-used-in-the-world that would be radically transformed.
The first
step of that revolution was the introduction of the electronic desktop
calculator in 1961. Although, mechanical desktop calculators had been available
since the turn of the Twentieth Century, by and large their use was restricted
to specialists—often called “computers” in businesses. [I actually had a
summer-job with British Petroleum as such a specialist in my last three years
at high school, and it was in my final year in that job that the office I
worked in acquired its first electronic desktop calculator and the British
Petroleum plant bought its first digital computer, both of which I learned to
use.] But with the increasing availability of electronic calculators, and in
particular the introduction of pocket-sized versions in the early 1970s, their
use in the workplace rapidly became ubiquitous. Mathematics underwent a major
change. Humans no longer needed to do arithmetic calculations themselves, and
professionals using arithmetic in their work no longer did.
It was
not too many years later that, one by one, electronic systems were developed
that could execute more and more mathematical procedures and techniques, until,
by the late 1980s, there were systems that could handle all the mathematical
procedures that constituted the bulk of not only the school mathematics
curriculum, but the entire undergraduate math curriculum as well. The final
nail in the coffin of humans needing to execute mathematical procedures was the
release of the mathematics system Mathematica in 1988, followed soon after by the
release of Maple.
In the
scientific, industrial, engineering, and commercial worlds, each new tool was
adopted as soon as it became available, and since the early 1990s,
professionals using mathematical techniques to carry out real-world tasks and
solve real-world problems have done so using tools like Mathematica, Maple,
and a host of others that have been developed.
Simultaneously,
colleges and universities quickly incorporated the use of those new tools into
their teaching. And while the cost of the more extensive tools put their use beyond most schools, the graphing calculator too was quickly
brought into the upper grades of the K-12 system, after its introduction in
1990.
Yet,
while the pros in the various workplaces changed over to the new human-machine-symbiotic
way of doing math with little hesitation, most educators, exhibiting very wise
instincts, proceeded with far more caution. The first wave of humans to adopt
the new, machine-aided approach had all learned mathematics in an age when you
had to do everything yourself. Back then, “computers” were people. For them, it
was easy and safe to switch to executing a few keystrokes to make a computer
run a procedure they had carried out by hand many times themselves. But how
does a young person growing up in this new, digital-tools-world learn how to
use those new tools safely and effectively?
To some
extent, the answer is (and was) obvious. You teach not for smooth, proficient,
accurate execution of procedures, but for broad, general understanding of the
underlying mathematics. The downplay of execution and increased emphasis on
understanding are crucial. Computers outperform us to ridiculous degrees (of
speed, accuracy, size of dataset, and information storage and retrieval)
when it comes to execution of an algorithm. But they do not understand
mathematics. They do not understand the problem you are working on. They do not
understand the world. They don't understand anything.
People,
on the other hand, can understand, and have a genetically inherited desire to
do so.
But just
how do you go about teaching for the kind of understanding and
mastery that is required for students to transition into worlds and workplaces
dominated by a wide array of new mathematical tools, where they will encounter
work practices that involve very little by way of hand execution of algorithms?
We know
so little about how people learn (though we do know a whole lot more than we
did just a few decades ago), that most of us with a stake in the education
business are rightly concerned about making any change that would effectively
be a massive experiment on an entire generation. So we can, and should, expect
small steps, particularly in systemic education.
In the
U.S., the mathematicians who developed the mathematical guidelines for the
Common Core State Standards made a good first attempt at such a small step.
True, it quickly ran into difficulties when it came to implementing the
guidelines in a large and complex public educational system that is answerable
to the public. But that is surely a temporary hiccup. Most of the problems at
launch came from a lack of effective ways to assess the new kind of learning.
Those problems can be and are being fixed. Which is just as well. For, although
it’s possible to argue for tinkering with specific details of the Common Core
State Standards guidelines, in terms of setting out a broad set of educational
goals to aim for, there is no viable alternative first step. The pre-1970s
educational approach is no longer an option.
In the
meantime, individual teachers at some schools (particularly, but not
exclusively, private schools) have been trying different approaches, in some
cases sharing their experiences on the MTBOS (Math
Twitter Blog-O-Sphere), making use of another technological tool (social media)
now widely available. [For a quick overview of one global initiative to support
and promote such innovations, the OECD’s Innovative Pedagogies for Powerful
Learning project (IPPL), see this recent article from the Brookings Institution.]
The
mini-course I gave at Nueva School in the San Francisco Bay Area last January,
which I talked about in the first of this short series of essays, is one such experiment in teaching
mathematics in a way that best prepares the next generation for the world they
will live and work in after graduation. I tested it first with a class of
non-science majors in Princeton in the fall of 2015 and then again with an
Adult Education class at Stanford in the fall of 2017. The Nueva School class
was its third outing.
With the
above backstory now established, next month I will describe that course and talk about how today’s pros “do the math”.
(Again, let me stress, I am not talking here about “pure math”, the academic
discipline carried out by professional mathematicians in universities and a few
think tanks. My focus here is on using math in the everyday world.)
In the
meantime, I’ll leave you with a simple arithmetic problem that I will discuss
in detail next time.
It comes
with two instructions:
- Solve it as quickly as you can, in your head if possible. Let your mind jump to the answer.
- Then, and only then, reflect on your answer, and how you got it.
The goal
here is not to get the right answer, though a great many of you will. Rather,
the issue is how do our minds work, and how can we make our thinking more
effective in a world where machines execute all the mathematical procedures for
us?
Ready for the problem? Here it is.
PROBLEM:
A bat and a ball cost $1.10. The bat costs $1 more than the ball. How much does
the ball cost on its own? (There is no special pricing deal.)