Can Data Mining Save America's Schools? - InformationWeek

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Software // Information Management

Can Data Mining Save America's Schools?

Schools have more data than ever, and there's a major push on to make better use of it to identify students who need help.

Using BI tools only to produce more elegant reports on No Child Left Behind mandates amounts to a wasteful "autopsy report," says Jim Hirsch, associate superintendent of academic and technology services for the Plano Independent School District. Instead, the Texas district with 68 schools and 54,500 students implemented a SAS Institute analytics system so it could draw in other measurements beyond the annual state standardized tests, including data from the schools' periodic student assessment exams, and try to predict what problems might lie ahead.

The district has been using SAS Enterprise Intelligence Platform BI tools for four years, but this is just its second year using them to not just look back at student performance, but also to "give insight into elevating performance," says Hirsch, who began a 34-year career in education as a math and programming teacher and has been in administration for 22 years.

With help from SAS, Plano created a data mart that brings in several sources of information, including Texas' annual state standardized test results and the Measures of Academic Progress testing results that are given to students in grades kindergarten through 10 multiple times a year.

Plano uses the SAS tools to analyze a variety of student data, looking at performance of entire schools, grade levels, groups of students (including subgroups, like those who speak English as a second language), and even individual students. Plano uses the software to create trajectory graphs showing how children are expected to perform several years ahead, taking into account their current strengths and weaknesses.

In one significant study in eight of its schools, it used that trajectory analysis to identify 60 students at risk of failing state standardized tests, and teachers developed plans to address their needs. Only 10 ended up doing poorly. "It was a huge success story," says Hirsch.

The technical challenges are less infrastructure-related and more about building an effective predictive model, Hirsch says, something that took Plano about two years to develop. "The highest priority is understanding what questions you want answered, what data is necessary to answer those questions, and to take advantage of the analytics," he says.

Parents access all student information via Plano's parent portal, where each family has individual, Web-based accounts that recognize them to provide appropriate access to children's records, says Hirsch. Parents can't run queries--"there's no legitimate way we could educate over 37,000 families in the proper way to combine variables and interpret the results," says Hirsch--but the reports include data visualization features such as learning growth charts.

The SAS system cost Plano $300,000, including license fees, hardware, and services, says Hirsch. Since it was deployed, Plano has been applying the software to analyze other problems, such as tracking credentials of teachers.

SAS also offers a hosted service for education analytics, but Hirsch sees an in-house data mart letting the district ask questions on the fly, build and test new analytical models more quickly, and integrate add-ons such as Futrix, multidimensional cube analysis software.

What questions might Plano explore? It's researching factors tied to training and credentials, such as what effect a science teacher's specialty in biology has on student performance. "There are many causal links to student achievement that need to be investigated now that we can correlate more data variables," says Hirsch.

Impact Assessment: Analytics In Education

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