The What Makes Schools Work Project Marisa Cannata, Ellen Goldring, Xiu Cravens, Roberto Penaloza, Vanderbilt University Mark Berends, University of Notre.

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The What Makes Schools Work Project Marisa Cannata, Ellen Goldring, Xiu Cravens, Roberto Penaloza, Vanderbilt University Mark Berends, University of Notre Dame Marc Stein, Johns Hopkins University These papers are supported by the National Center on School Choice, which is funded by a grant from the U.S. Department of Education's Institute of Education Sciences (IES) (R305A040043). All opinions expressed in this paper represent those of the authors and not necessarily the institutions with which they are affiliated or the U.S. Department of Education. All errors in this paper are solely the responsibility of the authors. For more information, please visit the Center website at June 2010

School Type Charter/TPS In-School Organizational Enabling Conditions Instructional Conditions Principal Leadership and Behavior Teacher Qualifications, Recruitment, and Hiring Classroom Conditions Academic Press Instr. Innovation Instr. Alignment Cognitive Complexity Achievement Gains School Context Conceptual Model 2

Examples of Research Questions How do leadership practices vary among school types? How much do organizational settings and teaching structures moderate the effects of school type on teacher professional community? Does the promotion of in-school organizational conditions and improved teacher press for learning in charter schools relate to student achievement? How do instructional practices differ between charter and traditional public school teachers? Who teaches in charter schools and why? 3

School Sampling Frame for Schools tested by Northwest Evaluation Association (NWEA)  Fall-Spring student achievement data  320 schools of choice  221 charter public schools  67 magnet public schools  32 private  5,864 traditional public schools  337 after applying matching criteria 4

Matching Criteria for Choice & TPS  School zip codes used to identify list of public schools  Same state  Geographic proximity  Grade level configuration  Percentage of students tested  School-level demographic data  Common Core of Data (CCD) ( )  Private School Survey (PSS)  Free and reduced price lunch  Race/ethnicity  Allowed many-to-many matches 5

School Participation & Response Rates  284 schools agreed to participate  Participation rate: 51% Charter, 49% Magnet, 53% Private, 34% TPS  Survey response rate  for principals was 78%  for teachers was 74% 6 CharterMagnetPrivateTPSTotal Participating schools Participating schools with principal response Number of teachers

Methodological Concerns What do we mean by a high quality match? –Difficulties in matching process Need for replacement schools Always of lower match quality –Explored match quality through final sample and two subsamples Matched pairs within 20 miles CS matched to TPS within 20 miles with closest propensity score Diversity within the charter sector –Affiliations with management organizations 7

Match Quality WMSW SampleDistance within 20 miles CharterTPSCharterAll TPSTPS w/min prop. score diff. Elementary grades.72.61* Middle grades.65.31*.64.27*.13* High school grades.30.15*.34.12*.13* White * *61.9 Black * *17.2* Hispanic Asian/Pacific Islander Am. Indian/Alaskan FRL * School size * *323.9 Students per grade * *53.6 N

Charter Affiliation WMSWDistance within 20 miles N%N% No affiliation Best Academy Special Needs Academy Other affiliations

Who Teaches in Charter Schools and Why? Teachers are most important resource for schools School choice theory predicts charter schools will use their flexibility to recruit different types of teachers Research Questions: How do teacher qualifications and characteristics differ between charter and TPS? How do teacher preferences for where to work vary by school type? 10

College Selectivity by Charter Affiliation WMSW sample Distance within 20 miles Min propensity score diff TPS All charters3.00*3.07*3.07 No affiliation3.26*3.21 Best Academy2.84*2.81*2.81 Special Needs Academy2.17*n/a Other affiliations

Teacher Job Preferences Final samplePairs within 20 miles CharterAll TPSCharterAll TPS Min prop. score diff. Principal support * *0.502* Agreeing with the school's mission * *0.144* Like-minded educators Autonomy over teaching * *0.202* Positive reputation * *0.292 At-risk students * Innovative instruction Job security * *0.202* Close to home * *0.350* Opportunities for advancement * * Small school * *0.152 N

Preference for Job Security WMSW sample Distance within 20 miles Min. propensity score difference TPS19.4%23.0%20.2% All charters16.4*11.6* No affiliation9.7*9.2* Best Academy24.3*19.4 Special Needs Academy34.3*n/a Other affiliations12.0*6.5* 13

Predicting Preference for Job Security WMSW sample Distance w/in 20 miles Min. prop. score difference Distance w/in 20 miles No affiliation ***-1.204***-0.975**-1.093** Best Academy * * Special Needs Academy 0.707n/a Other affiliations Pscore N Note: Other dependent variables include teacher qualifications and characteristics. 14

Conclusions Match quality does not matterMatch quality matters Affiliation does not matter CS teachers are less experienced, less certified, fewer advanced degrees CS teachers have a greater preference for agreeing with the school’s mission and less preference for working close to home As sample is restricted: TPS have fewer black teachers (and fewer than CS) TPS preference for school with positive reputation goes down (and more similar to CS) Affiliation matters Non-affiliated CS teachers have a greater preference for autonomy and less preference for principal support or job security Other affiliated CS teachers have less preference for principal support College selectivity, midcareer, gender, percent Hispanic teachers Preferences for at-risk students, innovative instruction, small school, like-minded educators, opportunities to advance

National Center on School Choice 16