Using State Data to Achieve Performance Goals

1. Archived Information Using State Data toAchieve Performance Goals REGIONAL HIGH SCHOOL SUMMITS MPR Associates, Inc. www.mprinc.com March-May 2004

2. Effective Performance Measurement Systems • Define valid and reliable measures of student performance • Use appropriate analytic methods • Promote school improvement

3. Essential Elements of NCLB • Adequate Yearly Progress • Assess state, district and school achievement over time • Identify schools in need of improvement • High School Performance Measures • Student achievement • Graduation rates

4. Essential Elements of NCLB • State Accountability System • Single system • Statistically valid and reliable • Populations • All Students • Subgroups of students

5. Defining Terminology

6. High School Graduation Rate In 2000, the high school graduation rate was 86 % • How is graduation determined? • How is student mobility treated? • When does measurement occur?

7. Measurement Criteria • Statistically valid systems • Single measurement approach • Accurate over time • Reliable data • Measure Construction • Fair • Useful

8. Analytic Considerations

9. Unpacking the Data Aggregate statistics can conceal useful information. Making the most of your data requires: • Identifying issues of concern • Disaggregating variables • Controlling for factors affecting outcomes

10. Example: NCLB Graduation Rate State and District Graduation Rate State District Grad. Rate 86 % 84 % Race-ethnicity White 89 90 Black 84 78 Hispanic 78 68

11. Example: NCLB Graduation Rate(continued) State and District Graduation Rate Urban State District Districts Grad. Rate 86 % 84 % 82 % Race-ethnicity White 89 90 86 Black 84 78 78 Hispanic 78 68 62

12. Example: NCLB Graduation Rate(continued) District and School Graduation Rates District School A School B Grad. Rate 84 % 92 % 78 % Race-ethnicity White 90 93 80 Black 78 94 74 Hispanic 68 NA 68

13. School Practices School Practices Student Outcomes Student Outcomes School Inputs School Inputs A General Model for Examining Student Outcomes Good Evaluation Focuses on more than Student Outcomes: Data on School Practices and Inputs are Also Essential

14. Essential Control Variables Examples: • School Practices • Curricular offerings and rigor • Class scheduling • Professional development • School Inputs • Student demographics • Size and urbanicity • Teacher experience

15. Additional Data Sources… …can provide a broader picture of student performance Examples: • Student Transcripts • Attendance • Subject area grades • Curricular rigor • Mobility & retention

16. Using Results to Promote Improvement

17. Improving Usability • User-tested reporting • Dedicated time for reflection and strategic planning • Building analytic capacity among teachers and administrators • Periodic feedback for overall design of state and local data systems

18. Conclusion

19. Effective Performance Measurement Systems • Track: Produce valid and reliable data on school and student outcomes • Analyze: Provide policy relevant information across a range of variables • Improve: Assist policymakers and educators in making better decisions