How to achieve scientific literacy


MATHEMATICS

Mathematics, like reading precedes science literacy. The importance of this statement should not be underestimated. Someone could argue, of course, that learning about Nature, say the importance of an insect in the food chain of an ecosystem, has nothing to do with mathematics. In the same way, there are probably thousands of topics of this kind, much in the sense of what we are used to see and 'experience' in a museum, on the Discovery Channel, or in a brochure of the local zoo. Most of these topics are visual feasts, appeal to our emotions (like astronomy, the sky and the 'heavens'), or are indeed a mixture of the two. We test science literacy with questions like 'does the sun revolve around the Earth or the Earth around the sun?', or the naming of an endangered species (or what the term actually means), or that a guy named Albert Einstein formulated the theory of general relativity. In learning these facts, there is no mathematics involved as far as the eye can see or the mind can fathom. And it is indeed possible to get some understanding of modern scientific facts without ever being involved in mathematical prove. But the truth is (and using this word can be problematic) that scientific fact has been subjected to mathematical treatment of some kind   -   counting (!) events or individuals, determining population means and distributions, classification and clustering species for studies of evolution, measuring and plotting temperature curves, measuring concentrations of a substance, describing the effectiveness of a toxin or the structure of a virus. 

It is not unusual that college students are afraid of mathematics in biology classes. After all they took biology to avoid math (at this level mostly algebra) and it comes as a surprise to some students that understanding a biological fact has always to do with understanding the mathematics used to corroborate it with experimental evidence. The latter is the distinguishing feature of science and can be said to be the repeated testing of an observation such as to prove reproducibility, i.e., predictability in the context of known circumstances. Numbers make the science world go round. And because reproducibility is key to scientific fact finding, statistics (i.e. math) is central to all things scientific. Statistics is adding and dividing and it has to be done to a degree of no non-sense activity, that is to say, in your sleep, to come to a correct conclusion. Science is not about being smart, or what ever this may mean, but to be accurate and tedious and the most needed yet most dreadful term for any scientist is 'control experiment'. Controlling means testing the influence of independent parameters by repeating an experiment again and again so as to separate fact from fiction. And the only way to prove that repetition shows consistent behavior is through statistical analysis. So all the facts we see and read about in museums, on TV, or in books are there because they have been shown beyond a reasonable doubt to be reproducible and consistent with observation and expectation. That an insect is an insect, the very existence of a food chain, or the prove that the Earth revolves around the sun, contrary to everyday experience. The latter comes from the success of geometry, a branch of mathematics that describes the form and behavior of usually imaginary objects like lines, dots, triangles, or parallel planes  in one-, two-, three-dimensional space. 

Scientific reasoning is abstract reasoning and it is often difficult for scientists to go beyond their specialized language (e.g. using mathematical formalism) to talk about their work. If they use mathematics in their talk, most people tune out. An unfortunate yet understandable fact. They key to scientific literacy, e.g. to understand why population genetics has a different quality than the book of Genesis, although depends on literacy in mathematics, or should I say a liking of mathematics. It is to show that numbers can represent a visual observation, quantify this observation, and that this quantification can later be used by someone else to make the same observation over again to say with confidence that it is the same observation. 


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Copyright © 2000-2011 Lukas K. Buehler