Taking the Guesswork Out of Teacher Hiring

Recently in Education Week, Madeline Will reviewed new teacher hiring practices designed to predict the longevity and effectiveness of teachers before they begin teaching. Excerpts from the piece appear below:

Sojourner and other researchers partnered with the Minneapolis school district to determine whether teachers’ resumes can predict how effective they’ll be in the classroom and how long they’ll stay. The researchers studied seven years of teachers’ resumes, as well as subsequent teacher-evaluation and retention data on hires. Researchers found that teacher applicants with relevant work experience were more likely to be effective and long-serving. And applicants who have a history of short tenure in past jobs were more likely to be poor performers. The researchers developed an algorithm to match job descriptions and titles on applicants’ resumes to the U.S. Department of Labor’s occupation data set. The data set is able to match occupations to the knowledge, skills, and abilities typically acquired in those positions.

Another strand of research is developing in Spokane, Washington. The 31,000-student district there created a two-phase screening system for teacher applicants. The central human resources office scores applicants based on recommendations and the experience and skills on their resumes. Then, principals look at the candidates who have met a particular cutoff score and do another round of evaluations before bringing prospective teachers in for interviews. A team of researchers found in 2014 that each of these screening processes had some predictive power in terms of teacher effectiveness. For instance, the effect on student achievement is roughly equivalent to being assigned to a second- or third-year teacher rather than a novice teacher

The small but growing body of research includes work being done in Los Angeles. In the 2014-15 school year, the district there adopted a standardized screening process for prospective teachers with eight components, including a writing sample and the delivery of a sample lesson. Applicants are scored based on rubrics, many of which are aligned to the district’s teacher-evaluation system. Researchers found the screening process is predictive of performance, as measured by contributions to student test-score growth, evaluation scores, and teacher attendance.

Research shows that urban districts can, on average, spend more than $20,000 on each new hire, which includes expenses related to recruitment, hiring, and training. It makes financial sense for districts to invest in selection mechanisms that help them predict which teacher applicants will be successful.

For more, see https://www.edweek.org/ew/articles/2019/03/13/taking-the-guesswork-out-of-teacher-hiring.html