Using Data to Improve Student Achievement Aimee R. Guidera Director, Data Quality Campaign National Center for Education

1. Using Data to Improve Student Achievement Aimee R. Guidera Director, Data Quality Campaign National Center for Education Accountability April 23, 2007

2. Framing Thoughts… Without data, you are just another person with an opinion….. Culture change underway in education community: View data not as a hammer, but as a flashlight.

3. The Power of Longitudinal Data Longitudinal Data — data gathered on the same student from year to year — makes it possible to: Follow individual student academic growth Determine the value-added of specific programs Identify consistently high-performing schools/classrooms/systems worthy of study

4. Longitudinal Data Systems & Accountability(the “reporting” aspect of accountability) With state longitudinal data systems, state approaches to accountability are enriched: Permits calculation of alternative accountability models such as growth; Facilitates more efficient collection/analysis of data for federal reporting requirements (grad rates, teacher quality, other NCLB reporting) Improves the quality of information on disaggregated data since all data doesn’t need to be collected separately each year Ensures all users of data are accessing/using the same data to conduct analyses/report rates

5. Longitudinal Data & a Broader View of Accountability With longitudinal data, states can have richer conversations about: Alignment of secondary education and postsecondary education and training (accountability through the education pipeline) Impact of teacher preparation/professional development on student learning (school of education accountability) Transparency of information on inputs and outcomes in education system (public/taxpayer accountability)

6. Longitudinal Data Systems and Improvement Efforts Longitudinal data systems also inform good decision making: Teachers, administrators are able to tailor instruction and programs to individual student needs. Policymakers are far better informed if based on student level data over time. Researchers can better evaluate impact of specific programs, approaches, pedagogy on student achievement.

7. Data Quality Campaign: Building Support and Political Will Among Policymakers to: Fully develop high-quality longitudinal data systems in every state by 2009 Increase understanding and promote the valuable uses of longitudinal and financial data to improve student achievement Promote, develop, and use common data standards and efficient data transfer and exchange

8. DQC Managing Partners Achieve Alliance for Excellent Education Council of Chief State School Officers Education Commission of the States The Education Trust National Association of State Boards of Education National Association of System Heads National Center for Educational Accountability* National Center for Higher Education Mgt Systems National Governors Assoc. Center for Best Practices Schools Interoperability Framework Association Standard & Poor’s School Evaluation Services State Educational Technology Directors Association State Higher Education Executive Officers *The campaign is supported by The Bill & Melinda Gates Foundation and managed by the National Center for Educational Accountability.

9. Creating a Longitudinal Data System 10 Essential Elements: Unique statewide student identifier (42, up from 36) Student-level enrollment, demographic and program participation information (46, up from 38) Ability to match individual students’ test records from year to year to measure growth (41, up from 32) Information on untested students (30, up from 25) Teacher identifier system with ability match teachers to students (16, up from 13) Student-level transcript information, including information on courses completed and grades earned (12, up from 7) Student-level college readiness test scores (9, up from 7) Student-level graduation and dropout data (40, up from 34) Ability to match student records between the Pre-K-12 and post-secondary systems (18, up from 12) State data audit system assessing data quality, validity, and reliability (36, up from 19)

10. Fundamental Design & (not so) Future Issues Regarding Quality Data Systems Fundamental Design Issues Privacy Protection Data Architecture Data Warehousing Interoperability Portability Professional Development around Data Processes and Use Researcher Access Future Issues Connect school performance with spending Connect school performance to employment and other systems Transfer records across systems and states

11. State of the State Data Systems

12. Policy Implications of Data Systems Does your system have the data system in place in 2005-06 to address these issues using student-level longitudinal data? Identify which schools produce the strongest academic growth for their students. (23 states) Know what achievement levels in middle school indicate that a student is on track to succeed in rigorous courses in high school. (5 states) Calculate each school's graduation rate, according to the 2005 National Governor's Association graduation compact? (26 states) Determine which high school performance indicators (e.g., enrollment in rigorous courses or performance on state tests) are the best predictors of students' success in college or the workplace. (4 states) Identify the percentage of high school graduates who go on to college take remedial courses. (14 states) Identify which teacher preparation programs produce the graduates whose students have the strongest academic growth. (9 states)

13. Data Quality Campaign Approach Build Policymaker understanding and will to invest in and use quality data infrastructures Success Stories—Case Studies of 4 states; Implementation Papers Recognition of leadership—Awards in November Provide tools, materials and information Examples of the powerful use of data to inform policy & practice Toolkits for various audiences on uses of data to improve achievement Quarterly Issue Meetings: June 2007 on Interoperability Create national forum to ensure collaboration, develop consensus and reduce duplication of effort Leverage existing efforts to maximize impact Collaborate/communicate through national partnership whenever possible One-stop resource center: www.DataQualityCampaign.org

14. DQC—Year 2Driving the USE of Longitudinal Data DQC will promote the powerful and indispensable use of data to all education stakeholders: Build longitudinal data systems with end users in mind Create toolkits for education stakeholders that demonstrate the power of longitudinal data Advocate for continued investments in state data systems Generate opportunities for states to learn from one another.

15. Questions? Aimee R. Guidera www.DataQualityCampaign.org aimee@DataQualityCampaign.org 952-476-0054 Thank You!