# Teaching math with context and applications

Most of us have gone through the paces of algebra through calculus in high school. I remember lots of problems and fact sheets. Sol Garfunkel and David Mumford imagine a math education system that teaches skills for the real world and increases quantitative literacy:

Imagine replacing the sequence of algebra, geometry and calculus with a sequence of finance, data and basic engineering. In the finance course, students would learn the exponential function, use formulas in spreadsheets and study the budgets of people, companies and governments. In the data course, students would gather their own data sets and learn how, in fields as diverse as sports and medicine, larger samples give better estimates of averages. In the basic engineering course, students would learn the workings of engines, sound waves, TV signals and computers. Science and math were originally discovered together, and they are best learned together now.

Right on. I like it. I think that’s how it ought to be.

This is a terrible idea that amounts to removing true mathematics in favor of subjectively chosen science and applied math courses.

It’s especially ironic coming from Mumford who advanced his own career through studying abstract mathematics. It’s especially disingenuous for Mumford, an algebraic geometer, to bemoan the “abstraction” of the quadratic equation. I’m sure their plan is great for creating grad student slaves but it sucks for creating original thinkers.

Why the choice of “finance, data and basic engineering”? If you want to revamp economics and physics courses, then fine. But why not revamp music and art as well? These are equally valid mathematical applications.

Please keep your politics out of my mathematics. A world without abstract reasoning is doomed to fail.

This is like complaining that your boss/wife/___ isn’t easy to understand in terms of how you’d like it/them to be.

Math is hard. But, life is hard too! Sorry! Now get back to work!

In my opinion Math & stat are sciences made to solve practical problems. Most of the best algorithms have been implemented to solve practical issues. The theories, the analytical approach, and the formal proofs are of course essential to understand where you can apply your “idea” and under which conditions it works. But during my academical path, I always tried to reformulate every formulas, theory and paradigm in a real and pragmatic workaday problem.

…And it is the same approach I’m following in my text and data mining blog at:

http://textanddatamining.blogspot.com/

Regards