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This comprehensive analysis explores the significant disparities in educational outcomes for minority students and the challenges faced in high-poverty schools. It highlights critical statistics, revealing that only half of minority students graduate high school and only 15% achieve bachelor's degrees within nine years of entering 9th grade. It discusses the importance of teacher effectiveness in shaping student success, addressing the maldistribution of teachers, the impact of teacher mobility, and the implications of performance incentives, guided by longitudinal data systems.
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Informing Policy: State Longitudinal Data Systems Jane Hannaway, Director The Urban Institute CALDER www.caldercenter.org
State of U.S. Education • ½ of minority students graduate from high school • 4 grade level gap between white and minority students by 12th grade • 15% of minorities earn BAs w/in 9 years of 9th grade
The WILL and the WAY • The WILL • Left, Right, Center • Agreement on education crisis • Strange bedfellows • The WAY • Few, but growing, guideposts
Finding the WAY with Evidence-A New Day- • Who has the evidence? • States have the makings of the evidence • Where are the makings? • State administrative data systems • Why do states have it? • Important effect of NCLB • Why important? • Address questions never before possible
Research Background: What We Know • Teachers matter- single most important schooling contributor to student outcomes • Wide variation in teacher effectiveness. Some teachers are simply much better than others • Standard measures of teacher quality not much related to effectiveness, but directly related to spending.
Research Background:What We Don’t Know • What is it about teachers that matters?
3 Research Probes • Teacher Maldistribution • Teacher Selection • Teacher Mobility
Teacher Maldistribution 1 • Comparison of VA of teachers in high/ low poverty schools • North Carolina and Florida • Findings • Low poverty - higher va, but not much • High poverty – larger variation in school
Teacher Value-Added at Percentiles by School Poverty Levels (North Carolina-Math)
Teacher Value-Added at Percentiles by School Poverty Levels (Florida- Math)
Novice teachers are less effective than experienced teachers. • Returns to experience taper off 3-5 years.
Distribution of Value-Added of Elementary Math Teachers in High Poverty Schools Solid line: Novice teachers Dash line: Teachers with 1-2 years of experience Dotted line: Teachers with 3-5 years of experience
Distribution of Value-Added of Elementary Math Teachers in Lower Poverty Schools Solid line: Novice teachers Dash line: Teachers with 1-2 years of experience Dotted line: Teachers with 3-5 years of experience
Teacher Maldistribution 2 • New York City • Phasing out of emergency certification • Introduction of alternative route teachers
LAST Exam Failure Rate of Elementary Teachers by Poverty Quartile, 2000-2005
LAST Exam Failure Rate of New Teachers by Poverty Quartile, 2000-2005
Predicted Effectiveness For Highest and Lowest Poverty Schools Narrows by 25%
Can change predicted effectiveness by selection up-front • Meaningful difference based only on attributes, though monitoring, development and selective retention also needed
Teacher Selection • Teach for America • North Carolina • Secondary school • Mainly math and science
TFA Findings – high school Student FE, Math subjects All TFA coefficients are significant at the .05 level.
Teacher Mobility • Mobility highest at most challenging schools • The worst teachers are the first to leave • General tendency to move to more affluent schools
Topic of the Day: Performance Incentives • Objective?? • Recruitment/ selection • Retention/ deselection • Increase performance thru effort
Issues • How good are the measures? • Individual vs school rewards? • Teachers without test scores?
VA Measures • Problems • Year to year variability • Measurement error • Sorting • How serious? • Less serious for policy research • More serious for individual stakes
Predicting Performance • Using first 2 yrs of performance – top to top/ bottom to bottom quintile • Goldhaber and Hansen (NC): 46%/ 44% • Koedel and Betts (SanDiego): 29%/ 35% • Sass (Florida): 22-32%/ 24-24%
Policy Implications • Use VA freely for research • Use VA carefully for individual teacher judgments • Important information • Corrorboration • More years are better • Move tenure decision out!
Research Questions • Are teachers in high poverty schools more/ less effective (value-added) than teachers in lower poverty schools? • Do school factors affect differences in the value-added of high poverty and lower poverty teachers? • Do teacher qualifications affect differences in the value-added of high poverty and lower poverty teachers?
Data • Florida (2000/01- 2004/05) • Elementary • Student achievement – FCAT-SSS • Grades 3-10 • Teacher links • Assignment, certification, experience, education • North Carolina (2000/1-2004/5) • Elementary • Student achievement • EOG – grades 3-8 • EOC – secondary subjects • Teacher linked through proctor and verification • Assignment, certification, experience, education
Definitions • High poverty elementary schools (>70% FRL students) • Lower poverty elementary schools (<70% FRL students) • Very low poverty schools (<30% FRL students).
NC Student-Teacher Link EOC student-level records Aggregate to EOC test classrooms by school, year, subject, proctor id Decision Rules Match if teacher and proctor id identical and fit statistic < 1.5.
Sample Restrictions • Exclude charter schools • Exclude schools that switch high poverty to lower poverty status • Only classrooms w/ 10-40 students • Only self-contained elementary classrooms
Analytic Sample Note: We focus on elementary schools, grades 3-5 where poverty information is most reliable. We exclude teachers from charter schools and we exclude classrooms with <10 students or >40 students in our samples.
Methodological Challenges • Non-random sorting of teachers and students • Distinguishing teacher and school effects • Precision in Teacher Effects Estimates • Sources of Teacher Effectiveness Differentials
Descriptive Findings: Student Performance * Differences between the given estimate and the corresponding estimates for schools with 70-100% FRL students significant at ≤ 5% and ** differences significant at ≤ 1%.
Distribution of Value-Added of Elementary Reading Teachers in Lower Poverty Schools Solid line: Novice teachers Dash line: Teachers with 1-2 years of experience Dotted line: Teachers with 3-5 years of experience
Distribution of Value-Added of Elementary Reading Teachers in High Poverty Schools Solid line: Novice teachers Dash line: Teachers with 1-2 years of experience Dotted line: Teachers with 3-5 years of experience
Differences between Lower- and High-Poverty by Percentile of Teacher Value Added
Teacher Value-Added at Percentiles by School Poverty Levels (North Carolina- Reading)
Teacher Value-Added at Percentiles by School Poverty Levels (Florida- Reading)
Sources of Difference in Teacher Value-Added Between High-Poverty and Lower-Poverty Elementary Schools
Sensitivity Analysis • School Effect • Empirical Bayes Adjustment
Conclusions • Teachers in high poverty schools, on average, are less effective than teachers in lower poverty schools. • Changing schools (high poverty/lower poverty) does not affect teacher effectiveness • There is greater teacher variation within high poverty schools than within lower poverty schools.
Conclusions (con’t) • Differences in teachers in High Poverty and Lower Poverty schools: • only weakly related to teacher qualifications • more strongly related to marginal effect of qualifications (experience) • not explained by school poverty level