TN school finds new tool to better organize data

Finding it difficult to evaluate school performance for the No Child Left Behind Act, the Hamilton County Department of Education (HCDE) turned to PASW Modeler data mining software from SPSS Inc. to find a better way to organize information and
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Finding it difficult to evaluate school performance for the No Child Left Behind Act, the Hamilton County Department of Education (HCDE) turned to PASW Modeler data mining software from SPSS Inc. to find a better way to organize information and report on their progress.

The HCDE’s nine K-12 school districts, comprised of 78 schools in and around Chattanooga, TN, are attended by over 40,000 students and 6,700 employees. As part of NCLB legislation, states supply districts with reports on student performance based on standardized state testing, but the HCDE administrators found that these reports consisted mainly of summary data that lacked range and depth of information. Students in the districts were scoring below state target levels, but administrators were having trouble pinpointing the reasons for poor performance.

The PASW Modeler data mining software allows the Department to look closer at student performance by combining data sources and exploring variables beyond what state reports provided. This helps administrators find warning signs of low performance and intervene as needed.

HCDE evaluates student performance early on in their school careers by analyzing test scores from students in grades three through eight. Using PASW Modeler, the Department was able to bring information from the district’s regional database (such as student attendance and test scores) into predictive models that show the expected level of performance for individual students, so that teachers are able to help students that might fall below the proficiency level. The analysis is automated, with data compiled and models run on a daily basis. The Modeler can also integrate information from each district’s database, so it’s possible to track one student’s performance even if they switch from one HC district to another.

In addition to pulling data for NCLB needs, the Department is also using the Modeler to run custom classroom reports, grade-level reports for grant applications, and school-level demographic and behavior reports. Being able to report and analyze this data has helped the Department share ideas for improvement.

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