Say you’re the superintendent of a K-12 school district, and you want every student in your district to be taught by a highly effective teacher. Shouldn’t you try to predict, before hire, which candidates are most likely to be effective in the classroom?

This is what the District of Columbia Public Schools (DCPS) set out to do in 2009 when it implemented a candidate-application process – TeachDC – that aimed to improve hiring by weeding out unqualified applicants and providing principals with a list of recommended candidates, according to a new study by Brian Jacob, Jonah E. Rockoff, Eric S. Taylor, Benjamin Lindy and Rachel Rosen. (Jacob also wrote a helpful summary of the study for Brookings.) In addition to submitting standard information such as academic credentials and GPA, TeachDC applicants are required to complete as many as three in-depth assessments.

The study found that measures collected as part the district’s TeachDC hiring process were predictive of candidates’ performance in the classroom, but that district principals didn’t always rely on that data in making hiring decisions.

So what can we learn from the experience in D.C.?

First, districts can improve their hiring practices. Even in a district like D.C., which has a strategic candidate-screening process in place, the data generated could be used more effectively. So just think about how much hiring could be improved in districts without such a system in place. The study acknowledges that the D.C. approach may be harder to implement in districts that are in smaller markets, have fewer qualified applicants or are looking to fill hard-to-staff positions. Even in districts that fit those criteria, however, a more strategic hiring process could help districts understand the strengths and weaknesses of incoming teachers before they ever step foot in a classroom. That data could be used in a host of ways: to guide placements within a school or district; to design a targeted induction process; or to assign teachers to individualized courses of professional development.

Second, this area is ripe for data-sharing partnerships between K-12 districts and educator-preparation programs. The study notes that districts have “considerable latitude” in what they require applicants to submit as part of the hiring process. Performance data gathered through the TeachDC assessments are valuable in guiding hiring decisions – but those type of data could also be valuable in helping educator-preparation programs understand the preparation levels and skills of their graduates.

Finally, if applicants to educator-preparation programs took the TeachDC assessments, would the scores predict whether those applicants were likely to become highly effective educators? At a minimum, the assessments and the scoring would have to be modified to adjust for the relative lack of experience of ed-prep applicants. But I can see at least three interesting benefits of an ed-prep application process that included substantive measures beyond grades and test scores. First, it could help identify candidates who have the potential to become strong teachers but wouldn’t be accepted to programs based solely on grades or test scores. Second, the process could help educator-preparation programs to better understand the incoming strengths and weaknesses of their candidates – and thus to identify where targeted support or remedial coursework might be appropriate. Finally, by incorporating districts’ hiring criteria, educator-preparation programs could start to align expectations with their K-12 partners and create a more coherent trajectory from pre-candidate to teacher of record.

From a district perspective, one way to improve teacher quality is to hire only the best candidates – and if there are ways districts can reliably identify those candidates, they should certainly do so. But another way to improve teacher quality is to transform the country’s educator-preparation system in ways that ensure all teachers graduate are prepared to be good on day one and great over time. Districts such as DCPS are collecting meaningful, actionable data through their hiring processes. Educator-preparation programs can – and should – learn from those districts to inform their own improvement efforts.

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