The Wisconsin Department of Public Instruction (DPI) School Financial Services team launched a new application to collect school district tax levy information. It replaced all prior paper reporting of levy amounts by fund and local municipality. Once data were submitted, the program automatically apportioned the total levy across municipalities, created individual municipal tax certification pages, and reported information to both DPI and the Department of Revenue. This application received accolades from the school district personnel, not only for its enormous time savings, but also for its ease of use and inter-departmental cooperation.

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Tax Levy Reporting Application: A shining example
of raising the bar on data collection (42.3 KB)

Districts have access to more data than ever. But how can districts create a consistent approach to using data to improve teacher effectiveness and student performance in every classroom? How can districts leverage their investments in data and reporting systems for student achievement?

This session will share how Jersey City, New Jersey Public Schools provides district administrators, principals, teachers, and support staff with skills, processes, and tools to transform data into actionable knowledge to improve instruction and student achievement.

Participants will be engaged in a discussion about the daily challenges in such areas as data management and analysis, instructional quality, professional development, student achievement, and Adequate Yearly Progress.

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Using the Data to Drive Improvement from the District to the Classroom
(8.68 MB)

This session is intended to provide an overview of the actions taken over the last three years to develop a statewide data system. Attendees will receive an overview of the setting of data standards and how they were implemented. Throughout the session the presenters will review the state solution and discuss the lessons learned and obstacles that had to be overcome to implement the state system. The session will also cover how the state assigns unique State Student Identifiers and real-time movement of data when students transfer within a district or to another district.

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Managing Student Data: Kentucky’s Statewide Solution (1.09 MB)

This presentation will focus on the process of placing Instructional Management Solutions (IMS) into the hands of school leaders, empowering them with data to help transform our schools. The audience will see a proven example of how a system was implemented to provide data quickly and easily to the hands of administrators, teachers, and parents-enabling them to change their perspective and conversations about student achievement. Teacher and parent efforts can now focus on specific information about student learning clearing the path to intervention planning, increased achievement, and improved schools.

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Developing a Data Driven Culture in School Districts (9.42 MB)

The National Center for Education Statistics online web-tool queries all the CCD data from 1986 to the present. The CCD data files (School, School District, School District Fiscal (F-33), State non-Fiscal, and State Fiscal) can all be accessed as part of an integrated relational database. This makes possible the longitudinal analysis of school, school districts, counties, Metropolitan Statistical Areas, and state education agencies. It also makes multilevel or vertical analysis across these levels possible. Currently data are available from 1986-1987 through 2003-2004. As each new year of data is released, it will be added to the Build-a-Table tool. We have recently added the 2000 Census data relevant for school districts, counties, and states to the Build-a-Table tool. We have also added data on school dropouts. The tool has been redesigned to manage larger volumes of data and an additional multilevel cross-tabulation feature has been added.

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Build-a-Table (BAT) (228 KB)

The most efficient way to meet today's information needs, the general public's demand for accountability, and the No Child Left Behind objectives is through the development of a comprehensive and dynamic common pK-12 data model. To date, the closest access to data models that schools and states have is in proprietary models developed by vendors and implemented in their software applications. Most states and school districts cannot make the necessary financial investment or do not have the technical expertise to develop such comprehensive data models.

Join in the conversation as we discuss the need for the development of a comprehensive education data model available to states and schools with the logical next step of a large-scale stakeholder engagement strategy. This future deliverable would not only facilitate local decision making but add to overall data quality by aligning data to be aggregated at the source. It would produce the "cleanest" data available while reducing the burden of designing and developing data models at district and state levels. It is critical that this engagement would involve all relevant stakeholders in data utilization at the national, state, local, and classroom levels.

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SIF: A Comprehensive pK-12 Data Model
Current Snapshot and Future Direction (692 KB)

Over the past two years, The Center for Data Quality (C4DQ) has worked with nine state education agencies on various data quality initiatives. In this session C4DQ will present its findings from the data quality practices and programs at work in these states. Topics to be covered include: performing effective data quality assessment and monitoring, using business rules and metadata to perform validations, enlisting the active participation of school districts, deciding how and where to correct data, and submitting high-quality data collections in a timely manner.

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Data Quality Best Practices at Work in the States (136 KB)

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