Much is often made about whether providing more technology in schools will benefit students or not, and that is a debate that will continue to rage. However, make no mistake, the adults in education, the administrators could certainly benefit from better data systems. In an article appear at eSchool News, Robert Brumfield reports on a effort to expand the use of longitudinal and financial data to improve school administration, accountibility and student performance.
The Data Quality Campaign (DQC) seeks to provide tools and resources that will help states develop high-quality data systems, while providing a national forum for "reducing duplication of effort and promoting greater coordination and consensus among the organizations focusing on improving data quality, access, and use."
the initiative is not just about using data to increase school accountability.
"We're also very much concerned about how to use data [to improve student achievement]," she said. "We want to make sure we have rich conversations about what it means for parents, educators, school board members, and other stakeholders to have longitudinal data, and what they can do with [this information]. Hopefully, we'll be able to provide answers to state policy makers about its value as they start building their systems."
Gathering longitudinal data, which the group defines as "data gathered on the same student from year to year," makes it possible to follow student progress through each grade, determine the value of specific schools and programs, and identify consistently high-performing schools so that educators and the public can learn from their best practices. DQC says longitudinal data also can help school leaders evaluate the effect of teacher preparation and training programs on student achievement and help school systems prepare more students to succeed in rigorous high school courses, college, and challenging jobs.
As a way of jump-starting its mission, the group has devised a list of 10 essential elements that every statewide longitudinal data system needs. They are:
- A unique statewide student identifier;
- Student-level enrollment, demographic, and program participation information;
- The ability to match individual students' test records from year to year to measure academic growth;
- Information on untested students;
- A teacher identifier system, with the ability to match teachers to individual students;
- Student-level transcript information;
- Student-level college readiness test scores;
- Student-level graduation and dropout data;
- The ability to match student records between the preK-12 and higher-education systems; and
- A statewide data audit system.
Modern database structures, for example, can easily accomodate such needs, with a little custom programming (I work with a database with a similar structure that can link people to companies to legislators to facitilies). The type of relational database is quite simple to design, quite complicated to program and test, but nonetheless, incredibly powerful. But
Fruth emphasized that the primary barrier to making this happen is rooted in policy, not technology: "From the tech side, it's easy to make leaps. Technology is always ahead of policy. But those are the barriers--not the technology itself."
Of course, all the data in the world is useless unless you use the data to measure that which you intend to measure. Much of the statistics thrown out about schools and education are largely irrelevant to the mission of schools--that is the education of children.
For example, per pupil expenditures seem like a useful measure, that is how much money are we spending, on average, to educate our children. But that doesn't take into account the failure rate we have. If, as studies show, an average of 30% of kids don't graduate from high school, how do we account for those lost dollars? Are they lost dollars? How do you measure financial success in education? How much money is spent on actual education of a child versus administrative costs? The breakdown is not readily apparent.
While improved data systems are important, equally important is re-thinking our metrics in education. Afterall, bringing the data doesn't mean anything if you can't interpret it in a meaningful fashion or apply to the education of kids.