Gifted Issues Discussion homepage Forums GT Research Correlation between math and science ability?

For many young people who aspire to be scientists, the great bugbear is mathematics. Without advanced math, how can you do serious work in the sciences? Well, I have a professional secret to share: Many of the most successful scientists in the world today are mathematically no more than semiliterate.

During my decades of teaching biology at Harvard, I watched sadly as bright undergraduates turned away from the possibility of a scientific career, fearing that, without strong math skills, they would fail. This mistaken assumption has deprived science of an immeasurable amount of sorely needed talent. It has created a hemorrhage of brain power we need to stanch.

I speak as an authority on this subject because I myself am an extreme case. Having spent my precollege years in relatively poor Southern schools, I didn't take algebra until my freshman year at the University of Alabama. I finally got around to calculus as a 32-year-old tenured professor at Harvard, where I sat uncomfortably in classes with undergraduate students only a bit more than half my age. A couple of them were students in a course on evolutionary biology I was teaching. I swallowed my pride and learned calculus.

I was never more than a C student while catching up, but I was reassured by the discovery that superior mathematical ability is similar to fluency in foreign languages. I might have become fluent with more effort and sessions talking with the natives, but being swept up with field and laboratory research, I advanced only by a small amount.

Fortunately, exceptional mathematical fluency is required in only a few disciplines, such as particle physics, astrophysics and information theory. Far more important throughout the rest of science is the ability to form concepts, during which the researcher conjures images and processes by intuition.

Everyone sometimes daydreams like a scientist. Ramped up and disciplined, fantasies are the fountainhead of all creative thinking. Newton dreamed, Darwin dreamed, you dream. The images evoked are at first vague. They may shift in form and fade in and out. They grow a bit firmer when sketched as diagrams on pads of paper, and they take on life as real examples are sought and found.

Pioneers in science only rarely make discoveries by extracting ideas from pure mathematics. Most of the stereotypical photographs of scientists studying rows of equations on a blackboard are instructors explaining discoveries already made. Real progress comes in the field writing notes, at the office amid a litter of doodled paper, in the hallway struggling to explain something to a friend, or eating lunch alone. Eureka moments require hard work. And focus.

Ideas in science emerge most readily when some part of the world is studied for its own sake. They follow from thorough, well-organized knowledge of all that is known or can be imagined of real entities and processes within that fragment of existence. When something new is encountered, the follow-up steps usually require mathematical and statistical methods to move the analysis forward. If that step proves too technically difficult for the person who made the discovery, a mathematician or statistician can be added as a collaborator.

FLATOW: Thank you very, very much. This is almost like advice to the lovelorn sort of book, it's advice to would-be scientists. Why did you write this?

WILSON: Well, 42 years of teaching at Harvard qualified me, and I had learned lot about what brings students into science, whether as professionals or as part of their general education program, and what drives them away. And I saw a lot of the brightest young people, the most qualified, potentially, to be in science and technology turned away because at an early stage in their career at Harvard they were just afraid of mathematics, and they were afraid of the kind of rigors that one experiences in the usual portrayal of scientists as white coat people standing at the blackboard explaining complex equations and other ideas to rapt audiences.

FLATOW: Because you talk about your career and about your work with such passion in your book that I few people would know that a scientist could be as passionate and as successful about their work. And it seems like it's a necessary - or it's something like, almost like continuing to have a childlike curiosity about the world for your whole life.

WILSON: Yeah, a passion, commitment to a subject, excitement over adventure, an entrepreneurial spirit. All these are more important than a very high IQ.

FLATOW: And you say there that the Mensa-level people really don't make good scientists.

WILSON: Well, I realize that this is one of the statements that has not proved controversial. Even my slight downplay of advanced mathematical fluency has not proved controversial. I've gotten a large number of responses on that, and almost - well, they're overwhelmingly favorable.

But the one on - I call it optimum brightness. I present it as just a conjecture, but I got it from a principle that I gradually evolved knowing a lot of very successful scientists and from my own experience, the following principle. The ideal scientist is bright enough to see what needs to be done but not so bright he gets bored doing it. And I've discovered as time goes on that some of the most successful scientists in America, the most innovative, have IQs in the low 120s.

And this began - this got me to start thinking about what happens to all these folks up in the 160, 170 IQ range that we hear about. So the conjecture says, well, it's too easy for them. And then that brings me then to the allusion you made to scientists - or that I've made - the ideal scientist thinks like a poet and works like a bookkeeper.

It's the poet, the poetic aspects of science, that seldom get talked about. But I've always felt that scientists fantasize and dream and bring up metaphor and fantastic images as much as any poet, as anyone in the creative sciences - art, the creative arts.

And the difference is that at some point, the scientist has to relate the dreams to the real world, and that's when you enter the bookkeeper's period. Unfortunately, it's the bookkeeper period which leads sometimes to months or years of hard work that too many prospective scientists and students interested in science see, rather than the creative period.

DD tested early as extreme math, though had no interest in it. Now at 11, she is loving Thinkwell pre-calc (still doesn't LOVE math though) She is more grade level in science, in her interests, and her understanding. We will see if physics helps, but basically, she makes up stuff to explain things and doesn't care what the actual truth is. Like that people have one stomach for solids and a separate one for liquids. Yes, she has been told, but she just forgets.

So, I'd have to say this anecdote does not support, and I'll comment that it probably depends on the particular area of science.

I hated arithmetic. Hated it. I think that much of my problem with math was self-fulfilling prophecy generated in no small part form those stupid timed fact-tests in 2nd through 4th grade. I was NOT a memorizer, never have been, so I was actually working the problems. Needless to say, one cannot actually DO that and finish 60-80 problems in 3 minutes. (I don't think it was actually the hundreds of problems that I recall. Visually, though, I'm pretty sure that it was a 6 or 7 by 10 grid.)

http://online.wsj.com/article/SB10001424127887323611604578398943650327184.html
Great Scientist ≠ Good at Math
E.O. Wilson shares a secret: Discoveries emerge from ideas, not number-crunching
by E.O. Wilson
April 5, 2013
Wall Street Journal

For every scientist, there exists a discipline for which his or her level of mathematical competence is enough to achieve excellence.