MPS High School Evaluation Council of the Great City Schools Annual Fall Conference October, 2010 Deb Lindsey, Milwaukee Public Schools Bradley Carl, Wisconsin Center for Education Research

High School Evaluation: Purpose, Design, Methodology Evaluation designed as comparisons between high school types (Small vs. Large, Charter vs. Non-Charter, etc.) –Not designed as a comparison/ranking of individual high schools –Not all schools included in some comparisons –Small/Large cutoff: 400 students –“Selectivity” defined somewhat narrowly: admissions requirement (4 schools)

High School Evaluation: Purpose, Design, Methodology 2 context measures (enrollment & demographics) + 11 outcome metrics (completion rate, test scores, attendance, suspensions, etc.) Time period generally through , corresponding to start of HS Redesign process Descriptive data + inferential (regression) analysis to account for differences in students served

High School Evaluation: Key Findings  Enrollment: distinct and purposeful shift toward smaller high schools  Corresponding increases in enrollment (numerical and “market share”) for several subsets of small high schools: small charters, small newly-created charters, etc.  Demographics: no evidence of any school types consistently under-serving student subgroups of interest (SpEd, ELL, etc.)

High School Evaluation: Key Findings WKCE Test Performance: –Stagnant rates of non-cohort proficiency on Grade 10 tests (% Proficient + Advanced); small increases in Grade 10 mean scale scores –Small schools appear to serve lower-performing students overall –Same-student gains (Grade 8-10; Fall 2005-Fall 2007 and Fall 2006-Fall 2008) for non-mobile students with matched tests: Most remain in same proficiency level, but more students drop 1+categories than increase No school types produce consistently superior gains for both Reading/Math for both growth cohorts; greater variation within school types than between

High School Evaluation: Key Findings  Mobility: higher rates of within-year mobility for Small sites, both descriptively (unadjusted) and inferentially (regression- adjusted):  Based on month-to-month changes in school of enrollment during and  Regression controls for student/school demographics + prior (grade 8) attendance & mobility  Variation in mobility again higher within school types than across school types

High School Evaluation: Key Findings Within-Year (September-May) Grade 9 Reading & Math Benchmark Gains: –Similar pattern to WKCE: no school type produces consistently superior gains, either descriptively or regression-adjusted; lower prior achievement in Small sites –Again, greater variation within than between types –Low participation rates may bias results

High School Evaluation: Key Findings Retention rates for first-time 9 th graders: Small schools have higher rates descriptively ( through ), but lower regression-adjusted rate for –Controls used in regression: student and school-level demographics & prior retention history (past 5 years) –Again, substantial within-type variance

High School Evaluation: Key Findings Attendance: 75-80% for grades 9-12 across school types; no significant change for most school types over past 5 years –Descriptive data: higher attendance rates (grades 9-12) for Large sites –Regression-adjusted data: higher for first- time 9 th graders in Small sites after controlling for demographics + prior (grade 8) attendance history –Again, large variance within school types

High School Evaluation: Key Findings GPA (overall and core subject): –Low GPA for all school types ( ); marginal (if any) improvement –GPA (both types) lower in Small sites; likely reflects lower ability levels upon entering high school

High School Evaluation: Key Findings High School Completion Rate: –Insufficient data to make meaningful comparisons (new schools/types + small student counts + high grade 9 retention rates) –“Total Quality Credits” (during Year 1 of H.S. and overall) used as proxy for progression through high school; higher TQC attainment in Large sites, but (again) substantial within-type variance

Conclusions Conclusion 1: very limited evidence of systemic improvement in high school outcomes studied Conclusion 2: some evidence that Small high schools overall serve different student populations (lower prior achievement, etc.) Conclusion 3: some high school types fare better on some outcomes, but very limited evidence of consistently superior outcomes for any school type across all years/metrics –Outcome variance generally greater within school types than across

Implications for HS Reform Change focus to a quality control/ performance management approach that encourages diversity of offerings + accountability for results –Select most valued/relevant outcomes, establish expectations, monitor results –MPS already taking steps in this direction: evaluating charters, EdStat, data warehouse reports, etc.