Investigating the Role of Human Resources in School Turnaround: A Decomposition of Improving Schools in Two States Acknowledgements: This research draws upon work performed under contract with the Institute of Education Sciences (ED-04-CO-0025/0020). This work does not necessarily represent the views of any affiliated institutions, and any and all errors are mine. Michael Hansen CALDER at the American Institutes for Research 6 th Annual CALDER Conference February 21, 2013 Washington, DC
2 The presumed role of human resources in turnaround Turnaround, transformation models Prescribe principal and/or teacher turnover Teacher and principal quality are most consequential schooling inputs Assume teacher/principal quality are static
3 Workforce turnover or human capital development? Which of the two models dominates in past turnaround schools? Results: Evidence of elements of both models playing a role Strong improvements among stable teachers Strong incoming teachers, no evidence on weak outgoing teachers
Longitudinal Data Sources Florida Math FCAT-SSS Student-teacher linked Spans to years North Carolina Math EOG tests Student-teacher linked Spans to years Principals 4
How is School Performance Identified? Time Span of Observation Window Monitoring PeriodBaseline Period CLPs TA MI NI
Descriptive Means of the Sample of Low-performing Schools 6 StateFloridaNorth Carolina School sampleElementaryMiddleElementaryMiddle Proportion of African American students 52.6%40.4%55.5%62.3% Proportion of Hispanic students21.6%31.6%12.9%9.2% Proportion of students ever eligible for free or reduced-price lunch program 89.8%83.2%74.4%69.5% Mean Student Achievement in Math Unique CLP, Non-TA Schools Unique CLP, TA Schools Total student-year observations43,55315,39837,37124,505 Note: Samples limited to student-teacher linked observations in math in chronically low-performing schools identified in Hansen and Choi (2012) using the 2005 turnaround point in math.
7 Decomposing Performance Improvements across Workforce Pre- vs. post-period Turnaround (TA) vs. non-TA 3 types of teachers in workforce: Outgoing Stable Incoming
Identifying Teacher Groups Contributing to Performance 8 Outgoing Incoming Stable Pre-periodPost-period
What Workforce Dynamics Turnaround Schools?
Teachers: Evidence Suggestive of Human Capital Development 11 StateFloridaNorth Carolina School sampleElem.MiddleElem.Middle TA*Post (β 5 ) 0.139**0.153**0.187**0.092** Outgoing*TA (β 7 ) Incoming*TA*Post (β 9 ) *0.014 Observations 43,55315,39837,37124,505 R-squared
Observed performance in NC Schools
Principals: Similar Evidence of Human Capital Development 14 School sampleNC Elem.NC Middle TA*Post (β 5 ) 0.154**0.065** Outgoing*TA (β 7 ) Incoming*TA*Post (β 9 ) Observations 39,39437,353 R-squared
15 Results are Robust to Alternative Specifications Are these results sensitive to: How teacher groups are categorized? How TA schools identified? No qualitative changes to the estimated relationships
16 Same Patterns of Improvement Observed in Other Schools? What about middling schools with low growth? How do they improve? Replicate identification and estimation in schools that have higher levels of status, but quick improvement in school growth Improvement of stable teachers most prominent in elementary schools; turnover in middle schools
17 Summary of Findings Results show strong, robust gains associated with stable teachers Evidence of high-performing incoming teachers, but not outgoing Does not necessarily vindicate either of two workforce models, but suggests mix or spillover
18 Important Study Limitations Descriptive investigation of outlier schools Not causal or representative Improvements are absorbed into staff, though other interventions may be at work Not an evaluation of specific treatment; not predictive of current efforts
19 Policy Implications Current policy emphasizes human capital turnover Best use of intervention efforts? Can these successes be replicated? Feeds into larger debate about teacher quality Costs of improvement vs. replacement Individual or context-specific effectiveness