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

Using Data to Improve Student Achievement
Aimee R. Guidera
Director, Data Quality Campaign
National Center for Education Accountability
April 23, 2007
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.
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
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
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)
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.
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
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.
Creating a Longitudinal Data System
10 Essential Elements:
1.
Unique statewide student identifier (42, up from 36)
2.
Student-level enrollment, demographic and program participation
information (46, up from 38)
3.
Ability to match individual students’ test records from year to year to
measure growth (41, up from 32)
4.
Information on untested students (30, up from 25)
5.
Teacher identifier system with ability match teachers to students (16,
up from 13)
6.
Student-level transcript information, including information on courses
completed and grades earned (12, up from 7)
7.
Student-level college readiness test scores (9, up from 7)
8.
Student-level graduation and dropout data (40, up from 34)
9.
Ability to match student records between the Pre-K-12 and postsecondary systems (18, up from 12)
10. State data audit system assessing data quality, validity, and reliability
(36, up from 19)
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
State of the State Data Systems
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)
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
DQC—Year 2
Driving 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.
Questions?
Aimee R. Guidera
www.DataQualityCampaign.org
[email protected]
952-476-0054
Thank You!