NEW YORK – Every industry will encounter challenges with hiring, because even the best-designed interview processes often cannot predict whether an applicant will succeed on the job. The stakes are greater when it comes to hiring public school teachers, where tighter budgets and heightened scrutiny of student performance magnify the need for an effective hiring model. But new research suggests that school districts may be undervaluing key predictive information already at their fingertips when making employment decisions.

In a study of hiring practices at the Washington DC Public Schools (DCPS), Jonah Rockoff, Senior Vice Dean for Curriculum and Programs and the Armand G. Erpf Professor of Business at Columbia Business School and his fellow researchers analyzed the robust data that DCPS collects on applicants and compared it with six years of job performance to determine the characteristics of top-performing teachers. They find that applicants’ past academic achievement, such as undergraduate GPA, and the quality of applicants’ written work and interviews, as evaluated by DCPS staff, are both strong predictors of future success in the classroom.

“Many factors ultimately determine educational success, but our research identifies an important opportunity to improve schools through a better teacher selection process. There is a clear correlation between a teacher’s prior academic achievement and cognitive ability and future performance in the classroom, and hiring systems that properly value these characteristics could see better results,” Rockoff said. “School districts – as well as hiring managers at all levels – need to develop systems that can better evaluate and optimize applicant data so that they hire employees who can succeed on the job.”

The study, Teacher Applicant Hiring and Teacher Performance: Evidence from DC Public Schools, co-written by University of Michigan Professor Brian A. Jacob, Harvard Graduate School of Education Assistant Professor Eric S. Taylor, Benjamin Lindy of Teach for America, and Rachel Rosen of MDRC, was published in the Journal of Public Economics. The final published paper builds on earlier announced results, using more years of data to support qualitative results and determine additional outcomes. The researchers studied over 7,000 teacher applicants to Washington DC Public Schools (DCPS), analyzing the applicant data, hiring decisions, and subsequent performance on teacher evaluations to identify correlations.

The researchers used the correlations to build an index of predicted performance – zeroing in on the profile of a teacher who would be most likely to succeed. If the district had followed this index for predicted performance, the researchers contend that 75 percent of the teachers actually hired from 2011-2013 would not have been hired under the updated system.

Other key findings include:

• Need for refocusing hiring factors: Researchers found that the factors which most strongly predicted future job performance did not have much influence on school principals when making their hiring decisions.
• Wide gap emerges in classroom performance: Based on their calculations, the researchers find that applicants who rate in the “top quartile” of their hiring model performed more than two-thirds of a standard deviation higher than those from the “bottom quartile.”
• Higher retention for “local” applicants: Teachers who attended undergraduate or graduate school in Washington DC were not higher performing than “non-local” applicants, but they were far less likely to leave DCPS in the initial years of employment.

In the time since results have been available, DCPS has used the results of the paper to help guide principals to promising candidates.

Professor Rockoff argued that the findings in education can carry over to other industries as managers build systems to screen and hire applicants.

“Hiring managers want to hire the best, but making that happen is often a challenge because of the many different ways you can identify what ‘best’ is,” Rockoff said. “As most roles require varied skills, there is a nuance to making the final decision – one that many organizations often don’t have the time to analyze. Evidence shows that creating a system of collecting highly-detailed applicant backgrounds will help managers understand which candidates are hired and how they perform and lead to hiring better performing employees.”

To learn more about the cutting-edge research being conducted at Columbia Business School, please visit www.gsb.columbia.edu.

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