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Concurrent Session VI Presentations

Thursday, July 12, 2012
11:00 am – 12:00 pm

VI–B: Washington State’s Use of the IBM Data Governance Unified Process Best Practices

Bill Huennekens, Washington State Office of Superintendent of Public Instruction
Eric Naiburg, IBM

    This session explores how the Washington State Office of Superintendent of Public Instruction has leveraged data governance best practices to better take advantage of its available information. Starting with the principle that data governance is “the discipline of treating data as an enterprise asset,” Washington State has taken advantage of the book The IBM Data Governance Unified Process to leverage the best practices outlined in the text and define a road map for continuous improvement. Attend this session to learn about the IBM process and how Washington State is using it to further develop their Data Governance Program.

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VI–C: Cross State Data Sharing—A Look at Regional Collaboration

John Kraman, Oklahoma State Department of Education
Bob Swiggum, Georgia Department of Education
Jay Pennington, Iowa Department of Education
Jim Campbell, AEM Corporation

    State education agencies have grappled for some time with the ever-increasing mobility of students across state lines. Modern state data systems have elevated the potential for cross-state data sharing to ensure that a student’s education remains uninterrupted regardless of their mobility. This session looks at three regional efforts and the objectives and challenges they represent.

VI–D: Moving Forward With Data Quality and Graduation Cohorts

Eva Shepherd, Ben Baumfalk, and Matt Heusman; Nebraska Department of Education

    Nebraska has employed a number of approaches to ensure data quality for Graduation Cohort data. The cohort process uses enrollment codes to determine if a student belongs to a school’s cohort. Districts can analyze their data using validation and verification tools that allow districts to look at multiple cohorts. This information aids them in forecasting and taking proactive action. It includes a longitudinal evaluation of students with multiple student IDs. This session provides an overview of the Graduation Cohort system design and the tools and training that allow districts to collaborate and analyze their cohort data.

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VI–E: Employment and Earnings Outcomes for Young Adult Bachelor’s Degree Holders

Grace Kena and William Sonnenberg, National Center for Education Statistics

    Using data from the American Community Survey, this session examines outcomes for young adult bachelor’s degree holders in employment and earnings. Methodological approaches as well as relationships between employment and earnings and characteristics including sex, race/ethnicity, nativity, and field of study will be explored.

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VI–F: Hawaii Partnership for Educational Research Consortium

Jennifer Higaki and Christina Tydeman, Hawaii State Department of Educations

    The Hawaii Partnership for Educational Research Consortium (HPERC) is a collaborative effort between the Hawaii State Department of Education and Hawaii’s research community to develop a common research agenda, build statewide capacity to conduct educational research, and leverage educational research opportunities within the state. Key elements of HPERC are an annual research symposium, an advisory committee of partnership organizations, and efforts to clarify and streamline the Hawaii State Department of Education’s research and data request processes. The presenters share strategies used to initiate the partnership as well as successes, challenges, and lessons learned.

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VI–G: Evaluation of Using Data Professional Development Program: Year 1 Implementation, Fidelity, and Evaluation Design

Linda Cavalluzzo and Laura Holian, CNA Education
Diana Nunnaley, TERC

    As states and districts increase the collection of student data, teachers are asked to use, interpret, and analyze data frequently. There are many books and professional development programs that purport to help teachers make use of student data to improve instruction and student achievement (Boudett, City, and Murnane 2010; Bernhardt 2009; Love 2008), but there is little rigorous evaluation of these programs. This randomized controlled trial of the Using Data professional development program was funded by the Institute for Education Sciences in 2010. This presentation describes the Using Data intervention, analysis plan, and preliminary Year 1 descriptive findings.

VI–H: Postsecondary Data: NCES Postsecondary Studies and Data Tools

Matthew Soldner, National Center for Education Statistics
Diana Nunnaley, TERC

    In this session, participants are introduced to the National Center for Education Statistics’ (NCES) suite of three postsecondary studies, its on-line data tool, and ways to gain access for advanced research using micro-level data. Attendees become familiar with the National Postsecondary Student Aid Study, used to describe how students and their families pay for education beyond high school; the Beginning Postsecondary Students Longitudinal Study, used to generate the national graduation rate and to better understand the relationship between student and institutional characteristics and college completion; and the Baccalaureate and Beyond Longitudinal Study, used to explore the early labor market outcomes of bachelor’s degree recipients and their decision to take additional education and training after the BA. After becoming familiar with the studies, participants arre introduced to PowerStats, an on-line data tool that uses these data sets to generate complex tables and simple linear and logistic regressions. Finally, attendees with interests in more advanced statistical methods are provided a brief introduction on how to request NCES micro-level data through the Center’s restricted-use data licensing program.

VI–I: Ad Hoc Query Tool

Carl Garber, Georgia Department of Education

    This session introduces attendees to the Georgia Department of Education’s ADHOC Query Report (tool). The ADHOC Query allows users to generate reports based on criteria selected by the user. Local education agencies (LEAs) can generate reports that show demographic, funding, enrollment, course, and program participation data, just to name a few. Come and learn about this new report “tool” and how LEAs can benefit from it!

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