Everyone knows about Florence Nightingale, whose 200th birthday is this year. You probably know of her courageous reform of hospitals and aid stations in the Crimean War, and her insistence on sanitary conditions for wounded soldiers that saved thousands of lives. You may know that she founded the world’s first school for nurses, and of her lifelong fight for the professionalization of nursing, formerly a refuge for uneducated, often alcoholic young women who had no other way to support themselves. You may know her as a bold feminist, who taught by example what women could accomplish.
But did you know that she was also a statistician? In fact, she was the first woman ever to be admitted to Britain’s Royal Statistical Society, in 1858.
Nightingale was not only a statistician, she was an innovator among statisticians. Her life’s goal was to improve medical care, public health, and nursing for all, but especially for people in poverty. In her time, landless people were pouring into large, filthy industrial cities. Death rates from unclean water and air, and unsafe working conditions, were appalling. Women suffered most, and deaths from childbirth in unsanitary hospitals were all too common. This was the sentimental Victorian age, and there were people who wanted to help. But how could they link particular conditions to particular outcomes? Opponents of investments in prevention and health care argued that the poor brought the problems on themselves, through alcoholism or slovenly behavior, or that these problems had always existed, or even that they were God’s will. The numbers of people and variables involved were enormous. How could these numbers be summarized in a way that would stand up to scrutiny, but also communicate the essence of the process leading from cause to effect?
As a child, Nightingale and her sister were taught by her brilliant and liberal father. He gave his daughters a mathematics education that few (male) students in the very finest schools could match. She put these skills to work in her work in hospital reform, demonstrating, for example, that when her hospital in the Crimean War ordered reforms such as cleaning out latrines and cesspools, the mortality rate dropped from 42.7 percent to 2.2 percent in a few months. She invented a circular graph that showed changes month by month, as the reforms were implemented. She also made it immediately clear to anyone that deaths due to disease far outnumbered those due to war wounds. No numbers, just colors and patterns, made the situation obvious to the least mathematical of readers.
When she returned from Crimea, Nightingale had a disease, probably spondylitis, that forced her to be bedridden much of the time for the rest of her life. Yet this did not dim her commitment to health reform. In fact, it gave her a lot of time to focus on her statistical work, often published in the top newspapers of the day. From her bedroom, she had a profound effect on the reform of Britain’s Poor Laws, and the repeal of the Contagious Diseases Act, which her statistics showed to be counterproductive.
Note that so far, I haven’t said a word about education. In many ways, the analogy is obvious. But I’d like to emphasize one contribution of Nightingale’s work that has particular importance to our field.
Everyone who works in education cares deeply for all children, and especially for disadvantaged, underserved children. As a consequence of our profound concern, we advocate fiercely for policies and solutions that we believe to be good for children. Each of us comes down on one side or another of controversial policies, and then advocates for our positions, certain that our favored position would be hugely beneficial if it prevails, and disastrous if it does not. The same was true in Victorian Britain, where people had heated, interminable arguments about all sorts of public policy.
What Florence Nightingale did, more than a century ago, was to subject various policies affecting the health and welfare of poor people to statistical analysis. She worked hard to be sure that her findings were correct and that they communicated to readers. Then she advocated in the public arena for the policies that were beneficial, and against those that were counterproductive.
In education, we have loads of statistics that bear on various policies, but we do not often commit ourselves to advocate for the ones that actually work. As one example, there have been arguments for decades about charter schools. Yet a national CREDO (2013) study found that, on average, charter schools made no difference at all on reading or math performance. A later CREDO (2015) study found that effects were slightly more positive in urban settings, but these effects were tiny. Other studies have had similar outcomes, although there are more positive outcomes for “no-excuses” charters such as KIPP, a small percentage of all charter schools.
If charters make no major differences in student learning, I suppose one might conclude that they might be maintained or not maintained based on other factors. Yet neither side can plausibly argue, based on evidence of achievement outcomes, that charters should be an important policy focus in the quest for higher achievement. In contrast, there are many programs that have impacts on achievement far greater than those of charters. Yet use of such programs is not particularly controversial, and is not part of anyone’s political agenda.
The principle that Florence Nightingale established in public health was simple: Follow the data. This principle now dominates policy and practice in medicine. Yet more than a hundred years after Nightingale’s death, have we arrived at that common-sense conclusion in educational policy and practice? We’re moving in that direction, but at the current rate, I’m afraid it will be a very long time before this becomes the core of educational policy or practice.
Photo credit: Florence Nightingale, Illustrated London News (February 24, 1855)
References
CREDO (2013). National charter school study. At http://credo.stanford.edu
CREDO (2015). Urban charter school study. At http://credo.stanford.edu
This blog was developed with support from the Laura and John Arnold Foundation. The views expressed here do not necessarily reflect those of the Foundation.
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my knowledge, no one ever did a randomized evaluation of the entire transformation model, with all components included. We did not find out what the joint effect was until the Mathematica study. Guess what? Sewing together swatches of sows’ ears did not produce a silk purse. With a tiny proportion of $7 billion, the Department of Education could have identified and tested out numerous well-researched, replicable programs and then offered SIG schools a choice among the ones that worked best. A selection of silk purses, all made from 100% pure silk. Doesn’t that sound like a better idea?
Yet if the lightbulb had been an educational innovation, it probably would have been proclaimed a dismal failure. Skeptics would have noted that only one out of six thousand filaments worked. Meta-analysts would have averaged the effect sizes for all 6000 experiments and concluded that the average effect size across the 6000 filaments was only +0.000000001. Hardly worthwhile. If Edison’s experiments were funded by government, politicians would have complained that 5,999 of Edison’s filaments were a total waste of taxpayers’ money. Economists would have computed benefit-cost ratios and concluded that even if Edison’s light worked, the cost of making the first one was astronomical, not to mention the untold cost of setting up electrical generation and wiring systems.
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