Why You Need Mental Arithmetic

There’s an argument in favor of teaching basic computational skills that starts something line this: The reason you need to be able to do arithmetic hand is that if your calculator ever breaks down…

If you ever hear a math teacher try to defend basic arithmetic facility on this basis, stop them right there and ask them if they know how to process coffee beans, dress a rabbit, smelt iron, and weave cloth.

Because that’s what the “if your calculator breaks down” argument comes down to. If civilization ever collapses, it’s important to know how to do arithmetic by hand. No question about that…but if we base our educational system on what we’d need if civilization collapses, perhaps we’d be better off teaching how to make a fire, grow wheat, or forge metal.

So why do we need to teach arithmetic? There are two reasons. The commonly given reason is that it prepares students for algebra. This is only partially true: done properly, learning arithmetic does prepare students for algebra. Unfortunately, what gets taught as arithmetic generally doesn’t do that. (Here’s the test: if you see no fundamental difference between 37 - 21 and 3x + 7y minus 2x + y, you were probably taught arithmetic correctly. If you see the two problems as different, you weren’t)

I’ve advanced this reason in my own classes, so you can take it as given that I believe it’s essentially valid.

But…it begs the question. Why should students learn algebra? The answer is that it’s a stepping stone to calculus, and that’s a requirement if you’re going into a STEM career.

This leads to an ongoing argument about this, based around the incontrovertible fact that most people don’t use algebra.

My response, rendered as a repostable meme:

why teach math

And that’s the problem. As I see it, the fact that most people don’t use algebra doesn’t mean that algebra isn’t important. It means that we need to encourage its use among those in nonSTEM fields.

But why? Let’s go back to arithmetic. Anyone can calculate with technology. But it takes initiative to break out the piece of technology, so most people don’t bother. This means they take numbers and accept or reject them on the basis of what they believe is true about the world: whether it’s that millions of illegal immigrants vote in elections, or that a Wakandan prince wants to get 25 million in gold out of his country.

What we need, as a society, are citizens who calculate as readily and naturally as they breathe. What that doesn’t require is the ability to do arithmetic by hand.

What it does require is the ability to do arithmetic mentally. The reason is this: if you need a device to perform arithmetic, be it a calculator or pencil and paper, computing requires an extra step beyond the computation: it requires taking out the device and setting it up. As a result, 9 times out of 10, you won’t do it.

On the other hand, if you see 7.98 + 3.15 and think to yourself, “Self, I I could do that in my head…”, then you’re much more likely to hear “Millions of illegal votes” and think “That means that a bunch of the people in the polling line with me weren’t legally registered…”

(Oh, and if you want to do 7.98 + 3.15 in your head, here’s how:  7.98 is two cents less than eight bucks, so figure:  8 + 3.15 = 11.15, minus two cents is 11.13.  I’ll do more about common core arithmetic later)



The Sixth Wave

Over the past four thousand years, four waves of mathematical innovation have swept the world, leading to rapid advances and significant changes in society:

  • The invention of written number (Fertile Crescent, 3000 BC).  This allowed civilization to exist, because if you want to live with more than your extended family, record keeping is essential…and that means keeping track of numerical amounts.
  • The invention of geometry (Greece, 300 BC).  Yes, geometry existed before then; what I’m using is the date of Euclid’s Elements, which is the oldest surviving deductive geometry.  The idea that you could, from a few simple principles, deduce an entire logical structure has a profound impact on society.  How important?  Consider a rather famous line:  “We hold these truths to be self-evident…”  The Declaration of Independence reads like a mathematical theorem, proving the necessity of revolution from some simple axioms.
  • The invention of algebra (Iraq, 900).  The problem “A number and its seventh make 19; find the number” appears in a 4000-year-old manuscript from ancient Egypt, so finding  unknown quantities has a very long history.  What algebra adds is an important viewpoint:  Any of the infinite variety of possible problems can be transformed into one of a small number of types.  Thus, “A farmer has 800 feet of fence and wants to enclose the largest area possible” and “Find a number so the sum of the number and its reciprocal is 8” and “The sum of a number is 12 and its product is 20” can all be reduced to ax^{2} + bx + c = 0 and solved using the quadratic formula x = \dfrac{-b \pm \sqrt{b^{2} - 4ac}}{2a}.
  • The invention of calculus (Europe, 1600).  Algebra is the mathematics of what is.  Calculus is the mathematics of how things change.  Calculus makes physics possible, and from physics comes chemistry and engineering.
  • The invention of statistics (Europe, 1900).  Both algebra and calculus deal with single objects:  a bridge, a number, a moving planet.  But the universe consists of many similar objects:  the human population; the planetary climate; the trash generated by a city.  Statistics aggregates the data on the individual in a way that can be used to describe a population…then uses the information on a population to predict information about an individual.  Everything in modern society, from the pain relievers you use to the road you travel to work, incorporates such a statistical analysis.

Many people, myself included, believe we are on the verge of a sixth wave.  That sixth wave will have the transformative power of calculus and statistics, and fundamentally reshape society.

The sixth wave is based around discrete mathematics.  That’s not mathematics you whisper in dark corners.  Rather, it’s the mathematics of things that can be counted as opposed to measured.  For example, length is continuous:  a length can have any value, and no one looks at you strangely if you say “I traveled 1.38924 miles today…”  (You might get some strange looks, but it’s because you specified the distance so precisely and not because of the distance itself)  But if you continued “…and met 2.35 people,” you would get strange looks, because the number of people you meet is a counted number:  it’s a discrete quantity.

How important is discrete mathematics?  If calculus is the basis for physics and engineering, then linear algebra is the basis for discrete mathematics.  But a first-year calculus problem would have a hard time solving even a simple question in statics (the physics of structures).  In contrast, Google’s search algorithm is based on mathematics learned in the first half of a standard college linear algebra course.

I’ll talk more about this later.  But if you’re interested in learning some linear algebra, the video lectures for the course I teach are available on YouTube.

The Most Important Letter

A question came up on Quora about what letter’s removal would have the greatest impact on the English language.  The obvious answer is “E”, since it’s by far the most common letter in English.

But let’s consider that.  Can you writ a comprhnsibl sntnc that dosnt us ths lttr?  Ys, you can!  So its not clear that “E” is all that important.

So let’s do some mathematics.  The key question is:  How much information does a given letter provide?    Consider the following:  I’m thinking of a color.  You know the color is either red, green, blue, or fuchsia.  (I have no idea what color fuchsia is…I just like the word)  Your goal is to determine the color I’m thinking of by asking a sequence of Yes/No questions.

One way you could do this is by asking “Are you thinking of red or green?”  If the answer is “Yes”, then  you might ask “Are you thinking of red?”  If the answer is “Yes”, then you know the color is red; if the answer is “No,” then you know the color is green (since I answered “Yes” to the first question).  On the other hand, if I answered “No” to the first question, then you know I was thinking of blue or fuchsia, so you might ask “Are you thinking of blue?”  A “Yes” tells you I’m thinking blue; a “No” tells you I’m thinking fuchsia.

Now reverse it.  If you know I’m thinking of the color red, then you have the answer to two Yes/No questions.  We say that “red” has an information content of two bits.

So far so good.  But suppose I’m somewhat dull and can’t think of any color other than red. In that case, you already know what color I’m thinking of, and don’t need to ask any questions.  In this situation, “red” has an information content of zero bits.

As an intermediate case, suppose that half the time I think of “red,” one-fourth the time I think of “blue”, and one-eighth the time I think of “green” and one-eighth the time I think of “fuchsia.”  Then you might ask a different sequence of questions:

  • Are you thinking of red?  (Half the time, I’ll answer  “Yes”, so the answer “red”gives you the answer to one question:  it’s 1 bit of information)
  • If the answer is “No,” then “Are you thinking of blue?”  Half the time this question is asked (remember it will only be asked if the answer to the first question is “No”), the answer will be “Yes,” so the answer “blue” gives you the answer to two questions:  it’s 2 bits of information.
  • If the answer is “No,” then the final question “Are you thinking of green?”  Again, half the time this question is asked, the answer will be “Yes,” which tells you that “green” is worth 3 bits; meanwhile, the answer “No” means I’m thinking of fuchsia, so “fuchsia” is also worth 3 bits.

It might seem difficult to determine the information content of an answer, because you have to come up with the questions.  But a little theory goes a long way.  The best question we could ask are those where half the answers are “Yes” and the other half are “No.”  What this means is that if n is the answer to the question p_{n} of the time, then the information content of the answer n will be -\log_{2} p_{n}.  Thus, if “red” is the color half the time, then “red” has an information content of -\log_{2} (1/2) = 1 bit.

So what does this mean?  “E” makes up about 12.7% of the letters in an English text.  But this means that knowing a letter is “E” answers very few questions.  So the letter E contains about 3 bits of information.  In contrast, “Z” only makes up 0.07% of the letters in an English text, so knowing a letter is “Z” answers many questions.  So the letter Z contains about 10.4 bits of information (the maximum).

At first glance, this suggests that “Z” may be the most important letter in the English language:  losing the letter “Z” will lose the most information.  However, there’s a secondary consideration:  “Z” doesn’t often appear in a text.  So every “Z” you drop from a text loses a lot of information…but you don’t drop that many.

And here’s where the greater prevalence of “E” comes in.  While the letter “E” only gives you about 3 bits of information, it’s common enough that dropping the letter “E” from a text will lose you more information overall.  For example, suppose you had a 10,000 character message.  Of these 10,000 characters, you might expect to find 7 Zs, and losing them would lose you about 77 bits of information.  In contrast, there would be almost 1300 Es, and losing them would lose about 3800 bits of information.


Exact is Not Accurate


Over the next few years, you’ll be certain to see a barrage of numbers thrown at you.  While researching the latest atrocity promoted by the administration, I came across the following tidbit:  The average tuition for private schools is $10,003.

Now, if I want to include this in a blog, vlog, Facebook post, or public speech, I have a conundrum.  Compare the two sentences:

  • The average tuition for private schools is $10,003.
  • The average tuition for private schools is about ten thousand dollars.

The first sounds like I know what I’m talking about:  that I’ve done some high-level research and wrestled a number to the ground.  The second sounds like I spent thirty seconds on  Google.  (Actually, the first number was based on thirty seconds on Google)

The difference is that I sound more convincing with the exact figure.  In fact, there’s a story (which might  or might not be true) that when the first surveyors found the height of Mount Everest, they came to a value of 29,000 feet…but they published it as 29,002, because that sounded more accurate.

The problem is the exact figure might not be accurate.  Consider the two statements:

  • The population of the United States is 324,595,182.
  • The population of the United States is 325 million.

The first gives an exact number, and sounds very accurate.  But it is almost certainly false.  In particular, even if the population of the US was 324,595,182 at some point, it is almost certainly not 324,595,182 right now.  On the other hand, it’s still about 325 million, and will be so for awhile.  (I talk about this in my FOCUS article).

There’s a concept in the sciences called significant figures.  The gist of it is this:  When I give you a number, I am giving you a guarantee that the non-zero digits of the number are correct.  (The zeroes are a little more complicated:  if you want a crash course on signficant figures, here’s the video I have my students watch)

  • If I claim 324,595,182, then I’m guaranteeing each and every digit is exact…and if the population is 324,595,183, then I’ve fed you misinformation.
  • If I claim 324 million, then I’m guaranteeing that the population is somewhere between 323,500,000 and 324,499,999 (since anything in this range would round to 324 million).

What’s the big deal?  One problem with statistics is that people don’t believe them.  You’ve heard the quote:  “There are three types of lies:  Lies, damned lies, and statistics.” I suspect part of the reason is that if someone says “The average tuition at private schools is $10,003,” they can respond with “But at our school, it’s $7500, so how do you get an average of $10,003?”   This generally leads to a discussion of how to calculate averages, and often degenerates into accusations of skewed samples.

On the other hand, if you say “The average tuition at private schools is around $10,000,” then to the person who says “But we only pay $7500,” the response is “Which is around $10,000.”  By avoiding the mechanics of computing the number, we focus on the value itself.

Math for Democracy

I surrender.

I’ve been trying to keep this blog politics free, or at least minimize the politics:  when I talked about the March Across the Hudson, I focused on estimating the crowd size and not on the reasons behind it.

I’m still going to minimize the politics.  But it’s clear that we’re heading towards a major crisis.  I’m not talking about the person in the White House, or Russian interference, or anything that minor.  I’m talking about the denial of basic fact-finding.

You’ve heard the term “fake news.”  The problem is that most Americans get their information from one or two sources, which they don’t verify.  If those sources are unreliable, then they’re going to get a warped view of the world.  So I have a new mantra:

Five minutes a day.

Take five minutes a day to track down a fact.  You might start with the news story, but don’t end with it.  Who did they interview?  If they’re reporting on a piece of research, track down the original article and check out the legitimacy of the publisher.  If they’re reporting on an incident, go to the local newspapers and see what their coverage is.  If they’re talking about waste in government spending, go to USAspending.gov and see how your money is spent.

So let’s talk about that.  One of the promises of the new administration is to drastically curtail the U.S. Department of Education, returning control of schools to the states. Sounds good, right?  But go to USAspending.gov to see how the Department of Education actually spends your money.  Note that I’m giving you the source, so you should feel free to check my claims.   (A guaranteed way to identify something as “not a fact” is that lack of a source:  If there’s no source, it’s not a fact.  Keep in mind this does not work in reverse:  you can cite a source and still spew non-facts)

Most federal agencies suck in a lot of taxpayer dollars…and then shovel them back to the states in the form of grants.  Find the government department you’re interested in, then download the grants database: this tells you who they’ve given money to, and how much.  You can import it into Excel, or download it as a CSV and  use your own spreadsheet software.  Then the fun begins…

You can sort the grants by any category you want.  The cost of the elected President’s recent trips to Mar-a-Lago have been in the news:  current estimates for the three weekend trips (out of five weekends in office) are around $12 million, so here’s a few grants made by the Department of Education that are around this much.  I’ve deliberately chosen programs that benefits states where Trump support was very strong:  yes, New York, California, and other states get money from the Department of Education, so of course we’re concerned…the point is that states that supported Trump need to be even more concerned, because here are some of the things they’re going to lose:

  • Nevada: $9,928,139 for Vocational Rehabilitation training. Nevada has received almost $200 million in grants from the Department of Education since January 1, 2016.
  • Kansas: $10,669,790 for Department for Children and Families for Vocational Rehabilitation training. Kansas has received more than $210 million in grants since January 1, 2016.
  • Texas: $11,187,178 to Bexar County Texas for “Impact Aid.” The army base Fort Sam Houston occupies a good part of Bexar County, and this land can’t be taxed, impacting the county’s ability to pay for schools. That’s money local taxpayers don’t have to pay.   The Department of Education has given more than $600 million in Impact Aid grants since October 2016, reducing tax burdens around the country.

Now for some math.  On a dollar basis, California, Texas, and New York have received the most from the Department of Education.  But they’re also the biggest states in the country.  An easily googlable fact is the population of these states; if you divide how much each states gets by its population, you obtain a per capita figure.

These are interesting.  A few more states that stand to lose big if Trump eliminates the Department of Education:

  • Alabama: $15,912,537 for preschool programs. Alabama received more than $400 million in grants. On a per person basis, that’s 26% more than Connecticut gets.
  • Louisiana: $9,177,379 for preschool education programs. Louisiana has received nearly $500 million in grants. On a per-person basis, that 37% more than California receives.
  • West Virginia: $9,828,491 for vocational and rehabilitation services. West Virginia has received more than $160 million from the Department of Education. On a per person basis, that’s 50% more than Massachusetts.


Lies, Damned Lies, and Statistics

We all know the quote:  “There are three types of lies: lies, damned lies, and statistics.”

But like many things that are short enough to tweet, this statement is misleading.

Statistics don’t lie.  People do, generally by omitting key pieces of information.   Any statistic worth repeating should include two other numbers.   If these are missing, the whole truth is being kept from you. 

The two numbers to look for are:

  • The sample size.  This is the number of cases examined.  If you base a conclusion on one example, you’re a politician or a pundit, relying on anecdotal evidence and shouting instead of facts and logic.  While a large sample won’t guarantee reliability,  a small sample will almost always be untrustworthy. 
  • The p-value.   This is a little more complicated,  but roughly speaking, it measures how convinced you should be.   A  small p-value (0.05 or less) means the evidence is very convincing. 

I’ll talk more about these later.  Until then,  remember: if someone doesn’t give you these values,  they’re not telling you the whole truth. 

Underreporting of Deaths

The White House released a listing of 78 terrorist attacks it claims were underreported by western media. Both the BBC and the New York Times have responded by posting links to the numerous stories they ran on these incidents, debunking the belief that these incidents weren’t reported in detail.

We can go further. The vast majority (56) of the terrorist attacks resulted in one or fewer deaths. Of these, only 19 people actually died; the remaining victims were wounded. The articles run by the New York Times on these 19 deaths had an average length of 705 words.

Of course, this number alone doesn’t tell us much. To be meaningful, we need some basis for comparison. One possibility is the average word length of articles on single murders. Unfortunately, there’s no shortage of such articles:

  • On February 6, 2017, a Virginia woman shoots her 6-year-old daughter.
  • On February 3, 2017, a 12-year-old shoots a store clerk in Arkansas.
  • On February 2, 2017, a 14-year-old girl shoots her brother over a video game in Toledo.
  • On February 2, 2017, two men shoot another man during a Craigslist robbery.
  • On January 9, 2017, a Florida police officer is killed.
  • On December 24, 2016, a man in Arkansas shoots at a car for tailgeting, killing a toddler.
  • On December 1, 2016, Joe McKnight is killed in what appears to be an incident of road rage.
  • On August 3, 2016, the body of Karina Vetrano is found in a Queens park.

I’m still collecting data, because it seems there’s a journal article here, but the preliminary data is too interesting to ignore.

These eight articles have an average length of 386 words. Actually, this figure is probably higher than the average for single murders: Joe McKnight was a NFL football player, and Karina Vetrano had considerably more coverage because of its local nature.

What this suggests is that if you’re killed by a terrorist attack, your death is likely to receive twice as much coverage as it would if you were merely killed as part of an ordinary crime. A similar analysis of stories from the BBC suggests that terrorist attacks get four times as much coverage as ordinary crimes.

Manufacturing and Mining

One of the oft-quoted statistics is that if it were an independent country, California’s economy would be among the ten largest.  In 2015, it was sixth, just behind the UK and just ahead of France.  Texas and New York are also major players:  Texas’s economy is slightly larger than Canada’s (in 10th place), while New York’s is just behind Canada.

However, there’s an important factor:  California (where I was born) is also more populous than New York (where I live) and Texas (where I have relatives).  Thus, while China’s economy is larger than New York’s, China has more people; as a result, the standard of living in China is lower.  From the ground, the important question isn’t “How much does my country make?” but rather “How much do make?”

For that, you want to look at the per capita figures:  that’s the total GDP divided by the total population.  I won’t do the comparisons for other countries, but only for California, New York, and Texas.  Under this comparison (again for 2015), New York comes out 2nd, California is 10th, and Texas is 13th.  Put another way:  If these states had the same populations, New York’s economy would be about 20% larger than California’s. (I’m using data from Wikipedia, if you want to play with the numbers yourself).

Now, unless you’ve been living under a rock, you know that the United States has a new President who’s rather controversial.   However, one of his campaign promises is that he’ll bring manufacturing and mining back to the US, and much of his appeal is in the so-called “Rust Belt,” where over the past twenty years millions of jobs have been lost.

Part of the argument is that the various free trade agreements made over the past forty years have destroyed manufacturing and mining, by making it easier to ship jobs.  That’s probably true, though almost every economist who’s studied trade has concluded that it also generates quite a lot of jobs here.  Again, the problem from the ground is that the jobs it generates are very different from the jobs that disappear:  It’s little consolation to a steelworker than the financial services industry is booming.

I’m going to take a look at one very specific industry, that seemed to support the new President very strongly:  coal.  In fact, one of the very first things the new government has done is ease regulations on coal mining companies regarding what they can dump into streams; this is being hailed as a way to re-open mines and get more miners to work.

Sounds good, right?  Except there’s a problem:  Productivity.

  • In 1985, the US coal industry produced about 900 million tons of coal, and employed about 180,000 workers.
  • In 2015, the US coal industry produced about 900 million tons of coal, and employed about 65,000 workers.

What should be clear from these figures is that coal mining jobs haven’t disappeared because they’ve been shipped overseas:  we’re producing as much coal as we did thirty years ago.  But we’re using one-third as many workers.  So what does this mean?  Reopening mines and restarting coal production will produce a bump in employment.  But the vast majority of coal jobs are never coming back.  

This problem is true across the spectrum:  technology is being used to get more done with fewer people.  We can bring back coal mining…but not the jobs.  We can bring back auto production…but not the jobs.  We can bring back textile manufacturing…but not the jobs.  The vast majority of manufacturing jobs are never coming back.

So what can be done?  We can revive the industry…but the jobs won’t be there.  We can take consolation in that other industries are booming…but that doesn’t help the displaced workers.

The only viable solution is education and retraining.  Rather than waste time, money, and effort trying to rebuild an industry that won’t employ many workers, it would be far more useful to spend that time, money, and effort to retraining our workers so they can build their own industries.


Problem Solving

In case you’ve been living under a rock for the past few years, you’ll know there’s something called “common core mathematics”, and that many states had adopted it while others have rejected it to produce their own state standards.  I won’t talk about the standards here (other than to say the biggest difference between Common Core and Your State Name Here Standards is the name).  Instead, I’ll talk about something that is part of the standards:  Problem Solving.


Unfortunately, mathematicians (and by extension, math educators) are terrible at producing names.   Chemists talk about adiabetic processes; biologists talk about glycophosphlipids; geologists talk about regoliths, and so on.  Meanwhile, mathematicians talk about sets, rings, fields, continuity, surfaces.  The difference is that mathematicians use these words in very specific ways.  One way to tell a mathematician is to see them cringe every time someone refers to a group of people…

So what about problem solving?  To ordinary people, this is a problem:  “Find 2398174 \times 139871.  But in the context of mathematics education, this is not a problem.  There’s no commonly accepted word for it, which is too bad (how you speak influences how you think:  see Neither Borrower Nor Lender Be),  so I propose the name “Task.”  Finding this product is a task:  You know how to do it, and it’s a question of following a set of steps to get the answer.


If 2398174 \times 139871 is not a problem, then what is?  It might come as a surprise, but this can be a problem: Find 4 \times 3.  It all depends on context.  If you know the multiplication fact 4 \times 3 = 12, then this is not a problem:  it is a task (specifically, the task of recalling what 4 \times 3 is equal to).  On the other hand, if you don’t know what 4 \times 3 is equal to, then this is a real problem.

So how can you solve this problem?  One way is to wait patiently until someone whispers in your ear “4 \times 3 = 12.”  But this relies on waiting for someone to give you the answer, and (from a broader societal perspective) programs you to believe what you are told instead of thinking for yourself; I’ve noted elsewhere that one of the reasons higher mathematics is important for a free society is that it develops the habit of questioning what you are told.

Instead of waiting for someone to give you the answer, you can try to solve the problem.  In this case, the problem solving might go something like this:

  • We’ve defined a \times b to be the sum of a bs, so 4 \times 3 is the sum of four 3s.
  • This means 4 \times 3 = 3 + 3 + 3 + 3.
  • But I know how to add:  3 + 3 + 3 + 3 = 12.
  • So 4 \times 3 = 12.

Ideally, the last thought is “Cool!  I can figure out mathematics on my own and not need to wait until someone tells me what to do!”

What’s important to understand is this:  Problem solving is a skill,and like all skills, it gets better the more you practice.  But you only get one chance to solve a problem.  That is to say, once you’ve solved the problem, then no variation on the same problem gives you a chance to problem solve, and you will never again have the chance to solve the problem.

(Admittedly, it’s possible to find a new solution to a problem.  But basic arithmetic has been around for thousands of years, so finding a new solution to the problem of multiplication is very difficult…indeed, finding a new solution to any problem is something that could earn you an advanced degree in mathematics)

Thus, once you’ve solved the problem of finding 4 \times 3 = 12, then 9 \times 7 is not a problem:  you’ve figured out how to solve it (in this case, as the sum of nine 7s).  In fact, once you’ve figured out 4 \times 3 = 12 this way, then you know how to solve 2398174 \times 139871and this question is not a problem anymore!

What does this mean?  Consider a traditional elementary school math lesson which shows students how to multiply two numbers using the standard algorithm.  The instant students are shown how to multiply two numbers using the standard algorithm, they lose forever the opportunity to solve the problem of multiplication.  They will never get another opportunity to solve the problem of multiplication.

This requires a substantial shift in viewpoint in how we teach students mathematics.  Traditionally, students have been programmed to apply certain Standard Algorithms for basic arithmetic operations.  This is ideal…if we want to create students who are programmed.  However, those who can only follow a program will be doomed when they confront something outside of their programming:  such students will never progress beyond their teachers.

Instead, we need to create students who are able to solve problems.   The only way to do that is to give them the opportunity to solve problems…which means holding off introduction of the standard arithmetic algorithms for as long as possible.

You might be concerned that this means students won’t be able to multiply 43 \times 15 without a calculator.  And that’s a legitimate concern.  However, let’s consider:

  • A student who hasn’t learned the standard algorithm for multiplying two 2-digit numbers can’t multiply 43 \times 15 without a calculator:  they have no way to even begin to answer this question.
  • A student who has solved the problem of multiplication can find 43 \times 15 without a calculator:  they can add forty-three 15s together.

The problem of 43 \times 15 exists independent of the student’s knowledge of multiplication.  The difference is the student who’s done problem solving will be able to solve the problem; the student who’s only learned how to apply algorithms will only be able to solve the problem they have an algorithm for.



Proof by Contradiction

I’ve written elsewhere about why higher mathematics is essential for maintaining a free society. I’m going to extend that idea by talking about a method of proof used by many mathematicians:  proof by contradiction.

Here’s an analogy that I give to my students:  Suppose you know that the bus you take to get home does not cross a river.  One day, you get on a bus to go home, and after awhile, you look out the window and see that you’re crossing the river.  You can immediately conclude you got on the wrong bus.

In proof by contradiction, we make an assumption:  we get on a bus.  We then follow the consequences of that assumption, wherever they take us.  If we ever obtain a result that contradicts something we know to be true, then we know that our original assumption was wrong.

For example, here’s a proof by contradiction:  If we multiply two numbers and get an even number, then at least one of the numbers had to be even.

The art of proof involves picking the right assumption to start with; in general, students will spend years learning how to navigate bus schedules.  I’ll shortcut that by sending you to the bus “Two numbers are odd.”  In this case, the destination of the bus is “The product of the two numbers is even.”

Let’s ride this bus for awhile.  If both numbers are odd, then the product of the two numbers is odd.  But the bus is supposed to end up at the destination “The product of the two numbers is even.”  It is impossible to get there on this bus!

So…we shouldn’t have boarded the bus “Two numbers are odd.”  Instead, we had to take any of the other buses:  in this case, “At least one of the numbers is even.”

How does this apply to maintaining a free society?  A key skill in building a proof by contradiction is entertaining a hypothetical situation, then considering all possible consequences of this situation.  If you don’t like the consequences, you’ll do everything you can to avoid getting on the bus.

So consider any political issue you want:  gun control, LGBTQ rights, reproductive rights, global warming, etc.  Consider any possible solution you want.  Then follow the consequences, not just to the point that you’re satisfied with its results, but as far as you possibly can.  If your solution leads to undesirable consequences, you might reconsider boarding the bus.  Conversely, if no consequence of your solution is objectionable, then it may very well be the right solution.