Concurrent Session VII Presentations

Thursday, July 18, 2013
1:45 pm – 2:45 pm

VII–B: Improving the Quality of School-Level Finance Data

Stephen Cornman, National Center for Education Statistics
Stephanie Stullich and Heather Rieman, U.S. Department of Education
Peggy O’Guin, California Department of Education)
David Uhlig, Charlottesville City Public Schools (Virginia)

Concerns about the equitable distribution of school funding within school districts have led to new federal data collections on school-level expenditures. The first of these was for the 2008–09 school year, as required under the American Recovery and Reinvestment Act (ARRA), and asked states to collect and report school-level data on both personnel and nonpersonnel expenditures. Subsequently, the Office for Civil Rights added a similar data collection to its Civil Rights Data Collection. Legislation has now been proposed that would change the Title I comparability provision to require districts to demonstrate that actual expenditures in Title I schools are comparable to those in non-Title I schools rather than to use proxies, such as student-staff ratios or estimates of school expenditures based on average teacher salaries. This panel will discuss the challenges of collecting finance data at the school level; current state and local practices for tracking and reporting expenditures at the district level and the school level; data quality issues that are evident in the school-level data collected thus far; and possible strategies for improving the accuracy and completeness of the data, such as developing standardized protocols for attributing costs to schools. Particular attention will be paid to the challenges that relate to collecting school-level data on nonpersonnel expenditures. These issues will be discussed from the perspectives of local and state fiscal coordinators as well as federal employees.

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VII–C: Data Analysis Technical Assistance Community of Practice in Education (DATA-COPE) Open Session

Dorothyjean Cratty, National Center for Education Statistics
Jared Knowles, Wisconsin Department of Public Instruction

This open session for the broad Data Analysis Community of Practice in Education (DATA-COPE) will support the exchange of information and resources for state and district education agencies and their partners. The focus of this exchange is on statistical methods for analyzing administrative data. This is not a policy or IT discussion session but an “in the weeds” methodological knowledge utilization session. Some of the areas of interest to the core DATA-COPE user group of state education agency (SEA) and local education agency (LEA) analysts are growth models, teacher effects, early warning indicators, student population projections, synthetic datasets, GIS data, data visualizations, and powerful descriptive analysis.

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VII–D: Let's Cross State Lines Without Getting Lost

Jay Pennington, Iowa Department of Education
Kathy Gosa, Kansas State Department of Education
Tom Ogle, Missouri Department of Elementary and Secondary Education

The state education agencies of Iowa, Kansas, Missouri, and Nebraska have been working together to build a foundation for data exchange. This eScholar Interstate ID eXchange project enables state administrators to locate students who may have continued school in a different state. This capability will aid in identifying false drop-outs and in more accurately reporting key education metrics. The panel members will discuss their progress and the technologies being used, including the Common Education Data Standards Connect tool. In addition, they will address the challenges encountered for their states, as well as the data policy and data governance issues that arose.

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Let's Cross State Lines Without Getting Lost (567 KB)

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VII–E: Rolling Thunder: Texas’ Methodical Approach to Flipping the Statewide Switch (CANCELLED)

Melody Parrish, Texas Education Agency

Flipping the switch on anything statewide in a state like Texas is a massive undertaking. This session will cover the phased-approach mindset that has undergirded all aspects of the Texas Student Data System (TSDS) project. Every aspect of the TSDS project—from technical development and limited production releases to communications and expectations management to bringing more than 1,230 districts on board—has benefitted from this methodical and measured approach. Hear the successes and challenges encountered during the last three years as well as practical tips for making your next effort more successful.

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VII–F: Using Longitudinal Data Through RTI and Data Team Processes to Inform Instruction and Support Services

Louis Cuglietto and Judy Diaz, Port Chester Public Schools (New York)
Mark Samis, Lower Hudson Regional Information Center
Shawn Bay, eScholar LLC

The presenters will discuss the use of longitudinal data to address Response to Intervention on the ground at John F. Kennedy Magnet School in Port Chester, New York. This presentation will address one of the pillars of the New York State’s Regents Reform Act regarding Data-Driven Instruction. Every aspect of the discussion will address the collection and analysis of data to inform instruction and support services. John F. Kennedy Magnet School is in the band of highest-need schools in New York and is a 2010 National Blue Ribbon School.

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VII–G: Massachusetts' Data Quality Program for Early Childhood Education and School Districtss

Rob Curtin, Massachusetts Department of Elementary and Secondary Education
Robb Geier, Public Consulting Group

Massachusetts’ Departments of Early Education and Care (EEC) and Elementary and Secondary Education (ESE) developed a Data Quality Program to help data collectors and data users understand and address the issues that may affect the production of high-quality education data. Participants in this session will learn how two state agencies collaborated to build a unified program that addressed education from birth through grade 12. This curriculum supports a larger program of data quality improvement that includes audits, flexible delivery models for training, tools for implementation monitoring, and individual local education agency support.

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Massachusetts' Data Quality Program for Early Childhood Education and School Districts (1.80 MB)

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VII–H: Massachusetts Early Warning Indicator System: Identifying At-Risk Students Across K–12 Trajectory

Kate Sandel, Massachusetts Department of Elementary and Secondary Education

After the positive response from districts to an early warning indicator provided to ninth graders, Massachusetts Department of Elementary and Secondary Education (MA DESE) created a datadriven Early Warning Indicator System designed to identify students in first through twelfth grade who are at risk of missing key educational benchmarks. MA DESE worked closely with American Institutes for Research to develop statistical models for each grade, leveraging state longitudinal data systems and using the state’s new P–20 platform to disseminate aggregate and student-level reports. This session will highlight the development process for this system, challenges addressed, and current efforts to support district use.

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Massachusetts Early Warning Indicator System: Identifying At-Risk Students Across K–12 Trajectory (981 KB)

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VII–I: Into the Future: Laying the Foundation for an Automated Teacher Licensure System

Matthew Bryant and Patty Pitts, Virginia Department of Education
Rona Jobe, Center for Innovative Technology
Corbin Fauntleroy,CNA Education

The Virginia Department of Education (VDOE) is upgrading its teacher licensure data system and is interested in developing an automated application system. Before developing the system, VDOE worked with technical and research experts to define the technological and data collection needs and a phased development process. This presentation will share the project’s results, reflecting information collected from interviews with other states and literature on the use of electronic signatures, payment and transcripts, and data elements that could be collected to support research on teacher preparation and effectiveness. Lastly, the presenters will discuss plans for and challenges faced in transitioning to automated processes.

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Into the Future: Laying the Foundation for an Automated Teacher Licensure System (313 KB)

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VII–J: Integrating A–F School Performance Grading Into a Statewide Longitudinal Data System (SLDS)

William Hurwitch, Maine Department of Education
Manos Stefanakos, Choice Solutions, Inc.

This session will show how Maine leveraged its statewide longitudinal data system data warehouse when building an A–F school grading system. Stakeholders, including the general public, can access their school’s grade through balanced scorecards or data tables and drill down for supporting longitudinal performance data or link to additional reports. The presenters will discuss the measures, business rules, and roll-out process and how the grading system ties to college enrollment, remedial course taking, and postsecondary persistence rates.

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Integrating A–F School Performance Grading Into a Statewide Longitudinal Data System (SLDS) (1.18 MB)

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