Access the best custom research to help hit your organization's goals. Set up your custom consult below in 60 seconds or less
to general questions, press inquiries, references, citations & more. Just fill out the form below and we.ll get back to you within 48 hours or less
March 12, 2014 by Hanover Research
The value of research in driving innovation in education cannot be understated.
We know that education leaders need big data to guide their decision-making processes. A recent Brookings Institution article suggests that development and use of state longitudinal data systems, acquisition of analytic capacity to best utilize data, and public demand for better evidence of program impact will drive the increased use of big data to empower schools to make data-driven decisions. Highlighted in these findings is the value of locally-derived data; according to Harvard education and economics professor Thomas J. Kane, this type of data will be more influential in local policy debates as “the impact of any intervention will depend on local conditions.” An example presented by Kane illustrates this point: “The effect of universal pre-school depends on the availability of non-subsidized alternatives, regulations governing program quality, the presence of skilled teachers—all of which may vary by site.” A key to big data, then, is making decisions based on data that represents the conditions in which the decisions will be taking place.
Big data is driving innovation in education. The conversation about this evolution is happening in a variety of venues all around us – in education journals, at research think tanks, even at SXSW. At a recent SXSWedu panel on data analytics, education leaders discussed the current gap between theory and practice related to the use of big data in K-12 education. Key topics discussed in this conversation include the value in asking the right questions to find the greatest utility in data (including sharing data with community stakeholders to develop a culture of sharing and community building); being able to quickly and efficiently translate data to actionable data to ensure that there is sufficient data available when making decisions and that the process of cleaning, managing, and merging the data is feasible; and building a culture of data despite the varying needs of teams that interact with the data (such as curriculum, data, and technology teams).
As you can see, the conversation around the use of big data as a tool to drive innovation in education is all around us.
We also know that researchers are focusing on the connections between teacher quality and student achievement. In recent months, reports from Student First, the National Council on Teacher Quality, and Education Week, among others, highlight the importance of teacher quality on student achievement. Research on the relationship between teacher quality and student achievement does not solely focus on immediate returns – this research addresses achievement over the lifetime of students, as research shows that quality teachers impact student achievement as well as student outcomes in adulthood.
The Measures of Effective Teaching (MET) study, funded by the Bill & Melinda Gates Foundation, explored “how a set of measures could identify effective teaching fairly and reliably.” A key finding of this research is that effective teaching can be measured. When adjusting the measures based on the backgrounds and prior achievement of students in each class, the study found that “the adjusted measures did identify teachers who produced higher (and lower) average student achievement gains following random assignment in 2010–11.The data show that we can identify groups of teachers who are more effective in helping students learn. Moreover, the magnitude of the achievement gains that teachers generated was consistent with expectations.” Further, the study found that “more effective teachers not only caused students to perform better on state tests, but they also caused students to score higher on other, more cognitively challenging assessments in math and English.”
A study by the National Bureau of Economic Research by researchers from Harvard University and Columbia University finds that the value-added (VA) approach accurately measures teachers’ impacts on student test scores. Following changes in teaching staff, the study finds that “when a high VA teacher joins a school, test scores rise immediately in the grade taught by that teacher; when a high VA teacher leaves, test scores fall. Test scores change only in the subject taught by that teacher, and the size of the change in scores matches what we predict based on the teacher’s VA. These results establish that VA accurately captures teachers’ impacts on students’ academic achievement and thereby reconcile the conflicting conclusions” of other researchers. Additionally, high value-added teachers improved their students’ long-term outcomes as students with higher VA teachers are “more likely to attend college, earn higher salaries, live in better neighborhoods, and save more for retirement.” Supported by these two key findings, the authors state that “teachers’ impacts on students are substantial.”
As we can see by this research as well as a wealth of additional research, rigorous research studies establish the connections between teacher quality and student achievement.
We know that big data is a tool to drive innovation in education and that teacher quality impacts student achievement. So how can we use big data to improve teacher quality with the ultimate goal of increasing student achievement?
A recent Forbes article on the use of big data in school districts nationwide identified key applications of big data to better prepare our nation’s schools to make data-driven decisions that impact student achievement. The Forbes article highlights the value of research to enable our education leaders to make data-driven decisions to impact student achievement through adaptive learning innovations, increasing educational donations, tracking long-term outcomes, and predicting teacher success. Building off the final initiative featured in the article – predicting teacher success – how can we use big data to better predict the success that teachers will have in the classroom? What role can big data play in improving teacher quality relating to the training of future teachers, the teacher hiring process, and improving professional development for teachers?
This is an exciting time for education research as these connections are made and big data is used in new and innovative ways to impact student achievement. The power, then, that this knowledge provides will no doubt further enable our education leaders to make well-evidenced, data-driven decisions to advance student achievement.