How do EDFacts Coordinators juggle their multiple responsibilities? How do they coordinate communications with program offices, organize processes for creating and submitting almost 100 files of various sizes (small to huge) and complexities, and keep track of all activities? This session will highlight management and communication strategies in three state education agencies.

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It’s a Juggling Act: EDFacts Program Management in SEAs (6.22 MB)

Arizona Education Data Warehouse—Content Development Methodology
Orion Gebremedhin, Sina Mowzoon, and Matt Smith, Arizona Department of Education

This session will present Arizona Education Data Warehouse (AEDW) methodology for: transformation of Arizona student source data, building derived facts and measures from source facts, Cube development, QA processes, user guide and data dictionary, and lessons learned.

Integrating Logic Models and Longitudinal Data Sets of Agency Performance
Steven Zwillinger, U.S. Department of Education

This session is designed for managers and program leaders (or those who support them) who are not mathematicians and do not have a statistics background. The session will provide systematic strategies to parse and examine a program's data by using the logic model as a framework by which to examine agency, trend and comparison data. The examples used to illustrate this process will be vocational rehabilitation data, but the techniques can be applied to virtually any educational program.

The momentum behind building high-quality data systems to harvest better information about student, school and district performance has never been stronger. Quality data are the foundation of any district's ability to develop strategies aimed at improving student success, and understanding how the state can support these efforts will help realize the potential of investments in longitudinal data systems at all levels. Attendees will hear from leading districts about their data-driven efforts and how state longitudinal data systems could better support their work.

New Hampshire Department of Education—Leading the Way for a Public Domain Education Data Warehouse—Including Student-Teacher Connections That Inform Instructional Change
Irene Koffink and Michael Schwartz, New Hampshire Department of Education
Jim Goodell, Center for Educational Leadership and Technology (CELT) Corporation

New Hampshire Department of Education (NHDOE) is developing its statewide longitudinal data system (SLDS) to fully meet its needs and also to benefit other state education agencies and school districts across the country. The New Hampshire SLDS, aligned with NCES and other national standards, will be released into the public domain.

The data warehouse is fed by a publicly available student data collection, along with a new Educator Information System and other proprietary source systems. The model was developed with P–20 in mind and will be further developed to support early childhood through workforce. The data warehouse also feeds Performance Plus, a system used by local education agency educators to inform instruction.

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New Hampshire Department of Education—Leading the Way for a Public Domain Education Data Warehouse—Including Student-Teacher Connections That Inform Instructional Change (1.37 MB)

Twenty Years With a Statewide Data System
Marshall Patton, Sara Ramesan, and Malinda Shanklin, West Virginia Department of Education

West Virginia began a mandated statewide data system at the beginning of 1991. The core databases have remained the same but data elements, standards, peripheral programs and collections continue to evolve. The presenters will discuss West Virginia's history and how a centralized system improves data integrity and quality, provide some insights and discuss the state's future.

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Twenty Years with a Statewide Data System (6.22 MB)

Is This Analysis Correct? Understanding the Link Between Data Quality and Analysis
Sean Mulvenon and Denise Airola, University of Arkansas

Data quality and use within and between educational systems is consistently identified as problematic. The automation of interactive or transactional systems to enter data has been shown to improve data quality, but many issues still persist regarding use. The purpose of this session is to demonstrate that data quality should be examined based on the intended analysis and use of the data. Several examples associated with No Child Left Behind (NCLB), school improvement, and re-rostering of data are provided.

What is data governance? Why should you care? Who should be involved? How do you develop a plan? The Data Quality Campaign (DQC) will provide an overview of the concept of data governance and the state of the nation based on 2009 survey results. Accompanying the overview will be on-the-ground examples from New Mexico and Arkansas. New Mexico will describe the development of its interagency Data Warehouse Council, and Arkansas will present the challenges and successes in developing its intra-agency governance structure within the Arkansas Department of Education.

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Data Governance: What, Why, Who and How (1.65 MB)

This session will look at ways the SIF Association is proactively embracing web services technology to provide more opportunities for interoperability in the K–12 space.

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SIF Web ServicesExpanding Interoperability Options (1.34 MB)