We can finally put “Scientifically Based Research” to rest. The term that appeared more than 100 times in NCLB appears zero times in the Obama administration’s Blueprint for Reform, which is the document outlining its approach to the reauthorization of ESEA. The term was always an awkward neologism, coined presumably to avoid simply saying “scientific research.” It also allowed NCLB to contain an explicit definition to be enforced—a definition stipulating not just any scientific activities, but research aimed at coming to causal conclusions about the effectiveness of some product, policy, or laboratory procedure.
A side effect of the SBR focus has been the growth of a compliance mentality among both school systems and publishers. Schools needed some assurance that a product was backed by SBR before they would spend money, while textbooks were ranked in terms of the number of SBR-proven elements they contained.
Some have wondered if the scarcity of the word “research” in the new Blueprint might signal a retreat from scientific rigor and the use of research in educational decisions (see, for example, Debra Viadero’s blog). Although the approach is indeed different, the new focus makes a stronger case for research and extends its scope into decisions at all levels.
The Blueprint shifts the focus to effectiveness. The terms “effective” or “effectiveness” appear about 95 times in the document. “Evidence” appears 18 times. And the compliance mentality is specifically called out as something to eliminate.
“We will ask policymakers and educators at all levels to carefully analyze the impact of their policies, practices, and systems on student outcomes. ... And across programs, we will focus less on compliance and more on enabling effective local strategies to flourish.” (p. 35)
Instead of the stiff definition of SBR, we now have a call to “policymakers and educators at all levels to carefully analyze the impact of their policies, practices, and systems on student outcomes.” Thus we have a new definition for what’s expected: carefully analyzing impact. The call does not go out to researchers per se, but to policymakers and educators at all levels. This is not a directive from the federal government to comply with the conclusions of scientists funded to conduct SBR. Instead, scientific research is everybody’s business now.
Carefully analyzing the impact of practices on student outcomes is scientific research. For example, conducting research carefully requires making sure the right comparisons are made. A study that is biased by comparing two groups with very different motivations or resources is not a careful analysis of impact. A study that simply compares the averages of two groups without any statistical calculations can mistakenly identify a difference when there is none, or vice versa. A study that takes no measure of how schools or teachers used a new practice—or that uses tests of student outcomes that don’t measure what is important—can’t be considered a careful analysis of impact. Building the capacity to use adequate study design and statistical analysis will have to be on the agenda of the ESEA if the Blueprint is followed.
Far from reducing the role of research in the U.S. education system, the Blueprint for ESEA actually advocates a radical expansion. The word “research” is used only a few times, and “science” is used only in the context of STEM education. Nonetheless, the call for widespread careful analysis of the evidence of effective practices that impact student achievement broadens the scope of research, turning all policymakers and educators into practitioners of science. — DN
Showing posts with label effectiveness. Show all posts
Showing posts with label effectiveness. Show all posts
Monday, March 29, 2010
Tuesday, September 22, 2009
Research as Innovation
Many of us heard Jim Shelton, the ED Assistant Deputy Secretary for Innovation and Improvement, speak to the education publishing industry last week about the $650 million fund now called “Investing in Innovation” (i3). Through i3, Shelton wants to fund the scaling up of innovations having some evidence that they’re worth investing in. These i3 grants could be as large as $50 million.
With that amount at stake, it makes sense for government funders to look for some track record of scientifically documented success. The frequent references in ED documents to processes of “continuous improvement” as part of innovations suggest that proposers would do well to supplement the limited evidence for their innovation by showing how scientific evidence can be generated as an ongoing part of a funded project, that is, how in-course corrections and improvements can be made to the innovation as it is being put into place in a school system.
In his speech to the education industry, Shelton complained about the low quality of the evidence currently being put forward. Although some publishers have taken the initiative and done serious tests of their products, there has never been a strong push for them to produce evidence of effectiveness.
School systems usually haven’t demanded such evidence, partly because there are often more salient decision criteria and partly because little qualified evidence exists, even for programs that are effective. Moreover, district decision makers may find studies of a product conducted in schools that are different from their schools to have marginal relevance, regardless of how “rigorously” the studies were conducted.
The ED appears to recognize that it will be counter-productive for grant programs such as i3 to depend entirely on the pre-existing scientific evidence. An alternative research model based on continuous improvement may help states and districts to succeed with their i3 proposals—and with their projects, once funded.
Now that improved state and district data systems are increasing the ability of school systems to quickly reference several years of data on students and teachers, i3 can start looking at how rigorous research is built into the innovations they fund—not just the one-time evaluation typically built into federal grant proposals.
This kind of research for continuous improvement is an innovation in itself—an innovation that may start with the “data-driven decision making” mode in which data are explored to identify an area of weakness or a worrisome trend. But the real innovation in research will consist of states and districts building their own capacity to evaluate whether the intervention they decided to implement actually strengthened the area of weakness or arrested the worrisome trend they identified and chose to address. Perhaps it did so for some schools but not others, or maybe it caught on with some teachers but not with all. The ability of educators to look at this progress in relation to the initial goals completes the cycle of continuous improvement and sets the stage for refocusing, tweaking, or fully redesigning the intervention under study.
We predict that i3 reviewers, rather than depending solely on strong existing evidence, will look for proposals that also include a plan for continuous improvement that can be part of how the innovation assures its success. In this model, research need not be limited to the activity of an “external evaluator” that absorbs 10% of the grant. Instead, routine use of research processes can be an innovation that builds the internal capacity of states and districts for continuous improvement.
-DN
With that amount at stake, it makes sense for government funders to look for some track record of scientifically documented success. The frequent references in ED documents to processes of “continuous improvement” as part of innovations suggest that proposers would do well to supplement the limited evidence for their innovation by showing how scientific evidence can be generated as an ongoing part of a funded project, that is, how in-course corrections and improvements can be made to the innovation as it is being put into place in a school system.
In his speech to the education industry, Shelton complained about the low quality of the evidence currently being put forward. Although some publishers have taken the initiative and done serious tests of their products, there has never been a strong push for them to produce evidence of effectiveness.
School systems usually haven’t demanded such evidence, partly because there are often more salient decision criteria and partly because little qualified evidence exists, even for programs that are effective. Moreover, district decision makers may find studies of a product conducted in schools that are different from their schools to have marginal relevance, regardless of how “rigorously” the studies were conducted.
The ED appears to recognize that it will be counter-productive for grant programs such as i3 to depend entirely on the pre-existing scientific evidence. An alternative research model based on continuous improvement may help states and districts to succeed with their i3 proposals—and with their projects, once funded.
Now that improved state and district data systems are increasing the ability of school systems to quickly reference several years of data on students and teachers, i3 can start looking at how rigorous research is built into the innovations they fund—not just the one-time evaluation typically built into federal grant proposals.
This kind of research for continuous improvement is an innovation in itself—an innovation that may start with the “data-driven decision making” mode in which data are explored to identify an area of weakness or a worrisome trend. But the real innovation in research will consist of states and districts building their own capacity to evaluate whether the intervention they decided to implement actually strengthened the area of weakness or arrested the worrisome trend they identified and chose to address. Perhaps it did so for some schools but not others, or maybe it caught on with some teachers but not with all. The ability of educators to look at this progress in relation to the initial goals completes the cycle of continuous improvement and sets the stage for refocusing, tweaking, or fully redesigning the intervention under study.
We predict that i3 reviewers, rather than depending solely on strong existing evidence, will look for proposals that also include a plan for continuous improvement that can be part of how the innovation assures its success. In this model, research need not be limited to the activity of an “external evaluator” that absorbs 10% of the grant. Instead, routine use of research processes can be an innovation that builds the internal capacity of states and districts for continuous improvement.
-DN
Subscribe to:
Posts (Atom)
