Jay Greene, discussing the use of evidence to inform policy, manages to range from the Gates Foundation’s Measures of Effective Teaching project to the evils of communism in a single blog post. Here’s the crux of his argument before it drifts off course:
I am now more aware of the opposite failing — believing that we can resolve all policy disputes and identify the “right way” to educate all children solely by relying on science. Science has its limits. Science cannot adjudicate among the competing values that might attract us to one educational approach over another. Science usually tells us about outcomes for the typical or average student and cannot easily tell us about what is most effective for individual students with diverse needs. Science is slow and uncertain, while policy and practice decisions have to be made right now whether a consensus of scientific evidence exists or not. We should rely on science when we can but we also need to be humble about what science can and can’t address.
Absolutely correct — as my colleagues Chad Aldeman and Kevin Carey explain, policymakers must use the best available evidence to make decisions — many times before the question is settled from a research standpoint.
But, Greene should be more ambitious about the evidence that we can develop and what we expect from research. Many other fields are making use of much more dynamic and rapid research cycles — providing not only more timely information, but also more fine-grained evidence about what works for particular subgroups and contexts (beyond just reporting the average).
At our recent event, The Next Decade of Educational Data, healthcare expert Lynn Etheredge described how health researchers, using digital technology and de-indentified electronic patient records, are building extensive research registries, making it possible, for instance, for the VA to detect kidney disease in veterans, often before symptoms emerge. Here’s how scientists are building a rapid learning research system for healthcare:
In education, Rhodes Scholar and learning expert Bror Saxberg adds that there is no lack of data being collected. But, the challenge is “putting it to work at scale and then learning from the data that comes in at scale.” He highlights the crucial connections among learning sciences research, the data the drives this research, and the way that this information should improve learning environments:
Saxberg and Etheredge begin to describe the rapid learning research approach that we need. And, as a bonus to Greene, done well, this approach would provide secure, open, and transparent access to data for a wide variety of researchers, avoiding the sole reliance on monolithic mega-studies that he fears.