Millions of educators have figured out important things about what and how to teach under different kinds of conditions -- but no system exists for them to contribute their bit of knowledge to the larger field in ways that help them and their colleagues get smarter and better.
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One of education's big problems is that the collective wisdom, insights, observations and experience of educators are pretty much squandered.

That is to say, millions of educators have figured out important things about what and how to teach under different kinds of conditions -- but no system exists for them to contribute their bit of knowledge to the larger field in ways that help them and their colleagues get smarter and better.

Well-organized schools and districts have systems to ensure that the expertise of faculty and staff is exposed and shared -- but most schools and districts are still organized around the long-standing tradition of isolated, autonomous practice.

Although this is frustrating for individual educators, the real problem with an inability to aggregate collective wisdom is that it means education has few ways to get better as a field.

All of which is why Learning to Improve: How America's Schools Can Get Better at Getting Better is a welcome addition to school literature. Written by Anthony Bryk -- the president of the Carnegie Foundation for the Advancement of Teaching -- along with Louis Gomez, Alicia Grunow and Paul LeMahieu, the book lays out a systematic way to roll up what it calls the "micro-expertises" of individual educators into the collective wisdom of the field.

The big idea of the book is that educators should come together in what it calls Networked Improvement Communities to focus on what the authors call a "high-leverage" problem, and then use the knowledge of individual educators, armed with relevant research, to tackle the problem and monitor progress. One of the keys is what the book calls "learning from variance." That is, if a program or practice is tried, and it works well in one place and not in another, that variance needs to be studied to understand what factors made the difference.

By starting very small and working in ever larger groups to develop hypotheses, test, monitor, learn from success and failure, and revise, the book argues that large-scale improvements are possible.

That's the theory, anyway, and Learning to Improve describes a couple of big efforts by the Carnegie Foundation to solve education problems.

The one I found most compelling is an attempt by a network of community colleges to improve their success rates. After what sounds like a crucial, if excruciating, effort to figure out all the root causes of the high rates of failure of community college students, the project settled on one particular focus for its work -- developmental (or remedial) math.

Developmental math is the undoing of many community college students, who often arrive after years of math failure. In fact, when the project began, only 5 percent of students in the network had successfully completed a credit-bearing math class within a year of taking a developmental math class.

Once they fixed on failure in developmental math as a high-leverage problem, the next step was a brainstorming activity among network participants. "Over and over," the authors say, "we ask, 'Why do we get the results observed?' Initial explanations are offered, and the cycle repeats, probing deeper: 'Well, why does that occur?'"

Folks in community colleges and the larger education community, including academic researchers, have thought a lot about this problem and have a lot of expertise to add. And when you aggregate their knowledge, it turns out there are many sub-problems, including:

  • Students often arrive thinking there's not much chance they will ever get "good at math."
  • Students often have difficulty registering for classes.
  • Adjunct faculty who tend to teach developmental math have little help in learning to teach.

"While one might contest any given reason ... one fact clearly stands out: no single person, process or resource is to blame," says Learning to Improve. Framing it as a systems problem takes it out of individual blame. Each piece of the system can then be tackled in ways that make sense given both research and practitioner knowledge -- and can be measured and studied.

For example, if you give students something to read that draws on Carol Dweck's work on Mindsets, will that change their attitude toward whether they can become good at math? One developmental math teacher tried it and found that it did have an effect on his students; others started as well and were able to map under which conditions it had a positive effect -- or no effect.

Many such micro-experiments, complete with data and analysis were conducted and rolled into the larger framework in ways that didn't conflict but instead complemented each other.

The end result: Instead of only five percent of developmental math students registering and passing a credit-bearing math class within a year, 50 percent did.

I am giving very short shrift to a complex and deep process that has a lot of aspects to it, but if you're interested in solving big problems in education in a way that honors the knowledge and expertise of educators in a methodologically rigorous way while addressing the larger systems in which educators work -- this could be a book for you.

Reducing the minority gap, or the income gap, in third grade achievement would be a great accomplishment. But it would count as a far greater success if every child learned to read by the end of third grade ....

The education field knows enough to achieve this goal. We just don't know how to organize our systems to execute on this goal consistently in every school and with every child ....

Leaders at all levels have a responsibility to create know-how on the job floor so that such valued accomplishments become regular occurrences rather than seemingly random events.

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