Title,Url,Last update date,Published at,First registered on,RCT_ID,DOI Number,Primary Investigator,Status,Start date,End date,Keywords,Country names,Other Primary Investigators,Jel code,Secondary IDs,Abstract,External Links,Sponsors,Partners,Intervention start date,Intervention end date,Intervention,Primary outcome end points,Primary outcome explanation,Secondary outcome end points,Secondary outcome explanation,Experimental design,Experimental design details,Randomization method,Randomization unit,Sample size number clusters,Sample size number observations,Sample size number arms,Minimum effect size,IRB,Analysis Plan Documents,Intervention completion date,Data collection completion,Data collection completion date,Number of clusters,Attrition correlated,Total number of observations,Treatment arms,Public data,Public data url,Program files,Program files url,Post trial documents csv,Relevant papers for csv Impacts of Selective Teacher Transfer Incentives,http://www.socialscienceregistry.org/trials/353,"April 16, 2014",2014-04-16 17:51:52 -0400,2014-04-16,AEARCTR-0000353,10.1257/rct.353-1.0,Steven Glazerman sglazerman@poverty-action.org,completed,2007-09-07,2012-10-30,"[""education"", ""teacher incentives"", ""value added""]",United States of America (10 districts in 7 states (all regions)),Julie Bruch (jbruch@mathematica-mpr.com) Mathematica Policy Research; Bing-ru Teh (bteh@mathematica-mpr.com) Mathematica Policy Research; Ali Protik (aprotik@mathematica-mpr.com) Mathematica Policy Research,"I20, I24, I28, J08","","We conducted a multisite randomized experiment in ten large and economically diverse school districts to test a novel approach to raising teacher quality in struggling schools. The intervention identified high-performing teachers using value-added measures (estimated impact of teachers on student test scores) in tested grades and subjects (math and reading or English language arts in grades 3 through 8) in each district and offered them $20,000 if they transferred to low-achieving schools and stayed there for at least two years. We randomly assigned teaching teams (grades in elementary schools and grade-subject combinations in middle schools) with vacancies within the low-achieving schools to a treatment group that are eligible to hire the high-performing teachers and a control group that will hire teachers as they normally do. The intervention had positive impacts on test scores in elementary schools, but not middle schools. Once recruited, high-performing teachers remained in their new schools at rates comparable to the control group. We also provide estimates of cost effectiveness showing large positive net benefits under plausible assumptions.","Description: Project landing page Url: http://www.mathematica-mpr.com/Education/tti.asp ","","",2009-03-16,2012-06-29,"The intervention is designed to proceed within each district according to the following steps. The first step is to conduct a value-added analysis* of student test scores to identify the highest-performing teachers, defined as the top 20 percent based on a value-added measure of teachers in tested grades and subjects in each district. The second step is to classify schools as “potential receiving” or “potential sending” schools. Potential receiving schools are those with the lowest achievement in the district, based on school-average test scores in the most recent year, and, in some cases, rankings on school accountability. The rare exceptions that are already participating in a comparable intervention are exempted. The rest of the schools in the district are potential sending schools. The third step is recruitment of (1) eligible high-performing teachers in sending schools, whom we refer to as “transfer candidates,” and, simultaneously, (2) principals of receiving schools. The highest-performing teachers (identified in the first step) in potential sending schools are offered a series of transfer incentive payments, totaling $20,000 over two years, to transfer into and remain in one of the receiving schools in their district. The offer is made to these teachers, known as “transfer candidates,” in the spring, at which point they are invited to apply to the program. At the same time, principals of potential receiving schools are invited to an information session and asked to identify likely teaching vacancies in targeted grades and subjects. To be considered for inclusion in TTI, principals must volunteer a vacancy. Eligibility is based on grade level and subject of the vacancy. A site manager in each district helps principals fill the targeted vacancies by providing information about transfer candidates and arranging and encouraging interviews. This extra hiring support is in addition to the TTI transfer incentive. Next, applicants must interview with and be offered a position by the receiving-school principal and then voluntarily transfer to qualify for the transfer incentive. To improve the probability of matching high-performing teachers with low-achieving schools, the implementation team works with each district to finalize offers and acceptances by early summer. Finally, the transfer teachers participate in a half-day orientation just before the start of the school year. Because they are selected on the basis of their performance in the classroom, it is assumed that they do not require additional formal support beyond what teachers normally receive. To facilitate the transition, however, the site manager provides informal support and answers any questions throughout the two school years of the intervention period. TTI teachers who fill study-assigned vacancies receive their first incentive payment after the orientation, and those who remain during the intervention period in the positions into which they transferred receive incentive payments in December and June, for a total of $20,000. Teachers who are identified as highest-performing but who are already teaching in low-achieving (potential receiving) schools are not eligible to transfer, but they are offered a retention stipend of $10,000 for staying at their schools over the same two-year period as transfer teachers. *Value-added measures seek to describe the contribution that teachers make (the value that they add) to student achievement growth, holding constant factors outside the teacher’s control, such as student background and prior learning (McCaffrey et al. 2004; Lipscomb et al. 2010). Lipscomb, Stephen, Bing-ru Teh, Brian Gill, Hanley Chiang, and Antoniya Owens. “Teacher and Principal Value-Added: Research Findings and Implementation Practices.” Cambridge, MA: Mathematica Policy Research, September 2010. McCaffrey, Dan F., J. R. Lockwood, Daniel Koretz, Thomas A. Louis, and Laura Hamilton. “Models for Value-Added Modeling of Teacher Effects.” Journal of Educational and Behavioral Statistics, vol. 29, no. 1, 2004, pp. 67–101. ","The main outcomes are math and reading test scores one and two years after baseline. Secondary outcomes are teacher retention in the school and in the district, measured by comparing teacher rosters at baseline and followup. Other outcomes include intermediate effects, such as the way in which students are assigned to classrooms, allocation of mentoring resources within the schools, and principal reports of collaboration and school climate. These outcomes are measured through a combination of administrative data, teacher surveys, and a principal survey.","",,,"The study is a cluster randomized design, with teams (defined below) as the clusters to be randomized and the units of intervention, with students or teachers as the unit of outcome measurement in most cases. The research identified eligible ""teams"", defined as grade level within an elementary school or grade-subject within a middle school. To be eligible, a team had to be in a low-achieving school and had to have at least one expected classroom teaching vacancy into which a new teacher could transfer or be hired. The researchers randomly assigned teams to either a treatment group where the principal could hire from a pre-selected pool of high value added teachers who were incentivized with $20,000 if they transfer, or a control group where the principal had to fill the vacancy the way he or she normally would.","",Randomization conducted by the researchers using computer-generated random numbers.,"The unit of randomization and of intervention is the ""team,"" defined as a grade within an elementary school or a grade-subject within a middle school. THis is very similar in many cases to randomizing schools, but we focus on the grade level where there was a teaching vacancy. In middle schools we focus on the grade or subject, which can be either math or English language arts.",165 teams,"Approximately 17,000 students",85 treatment teams and 80 control teams,"","",None,,true,,"",false,"","",,"",false,"","","Abstract: Citation: URL: http://www.mathematica-mpr.com/publications/redirect_pubsdb.asp?strSite=pdfs/education/TTI_fnlrpt.pdf Abstract: Citation: URL: http://www.mathematica-mpr.com/publications/redirect_pubsdb.asp?strSite=pdfs/education/tti_high_perform_teachers.pdf "