Conrad Wolfram is a brilliant mathematician. He has written a book which argues that math education should not focus on how to compute various things, but on the thinking behind the computation. This article describes in breathless wonder Wolfram’s equally breathless idea to change how math is taught in order to keep up with the real world.

Wolfram makes the case that computation thinking is required in all fields and in everyday living—and that no one does calculations by hand. We’re living in what Wolfram calls a “computational knowledge economy” where the education question is, “How to prepare young people for a hybrid human-machine world?” In this new age, it’s not what you know, “it’s what you can compute from knowledge,” argues Wolfram.

It is a brave new world that Wolfram envisions, getting away from what he views as rote memorization and to the actual solving of real-world problems.

And perhaps for Wolfram, he had a “deep understanding” of mathematical processes at an early age, though I find it hard to believe that he never had to learn the basics somewhere along the line to get to his present state of development.

A key red-flag in this article is this:

Wolfram joins leading math educator Jo Boaler and economist Steven Levitt as leading voices advocating for change. “Put data and its analysis at the center of high school mathematics.” That’s the conclusion of a paper by Boaler and Levitt. They recommend that “every high school student should graduate with an understanding of data, spreadsheets, and the difference between correlation and causality.

Boaler and Levitt argue that we need to get away from the traditional sequence of algebra-geometry-precalc-calculus, and focus more on data and statistics.

The problem with brilliant people like Wolfram is that they often fool themselves with their own brilliance and convince themselves that they know more than they do about subjects in which they have no expertise. Such a person is called ultracrepidarian which is defined as “noting or pertaining to a person who criticizes, judges, or gives advice outside the area of his or her expertise”.

Like many math geniuses, Wolfram appears to have forgotten his own consolidation phase. He makes it sound as if mastery of mathematical concepts is a lot simpler if we strip out the computation aspect of it. But a person who may be extremely talented at doing computations, may not move through unfamiliar material with the same ease.

For the multitude of people who lament that they were never good at math, the pie-in-the-sky revelations of people like Wolfram, Boaler and Levitt have appeal. Their arguments are seductive and draw people in to an “if only I had been taught math this way” narrative. The Wolframs, Boalers and Levitts are welcomed to an edu-establishment that continues to extol ineffective practices to an ever-growing audience that unquestionably embraces them.

Follow the money.

Like Bill Gates, there’s a tendency for people like this to view education as pathways into their product worlds. They want to develop “users”, and that word has a lot of bad connotations. They see education in terms of statistical averages, not as equal pathways to whatever individual students could be.

Many adults don’t need calculus or even algebra, so why push it? Many will need to be able to use computer tools, so why push mastery of the algorithmic steps? They seem to ignore the fact that they’re proposing a vocational educational model that starts in Kindergarten. So who are the few who get the opportunity to delve deep into math, science, and engineering? Probably their kids.

The only solution is choice.

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NZ teaches a lot more statistics than most countries, and we also have the ability to use whatever technology we want. So I teach correlation to my students using computer drawn graphs and with automatically calculated coefficients. I’m happy with that, since plotting graphs is not useful work when I could be teaching them material.

But when we come to analysing the results, we suddenly need core maths again. The line of best fit’s gradient means something important. But students who missed all the work on lines back around Year 10 are flummoxed — they have the equation of the line, but they have no idea what it means. Wolfram will think it “obvious”, but then he’s never had to teach it to a less than brilliant seventeen year old.

Moving to statistics over calculus and computers over hand calculated doesn’t get away from the need to have solid core skills. Having taught it for years, I know that students without good algebra and graphing end up doing their statistical analysis by rote learning, because they have no other option. Precisely what Wolfram wants to avoid.

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Reblogged this on Nonpartisan Education Group.

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