Nimble Partners with Researchers to Identify Excellent Teachers

Written by 
Lauren Dachille

Nimble Partners with Researchers to Identify Excellent Teachers

I founded Nimble with a vision for the future of K-12 talent. Across industries, I saw data science being used to improve decision making — from which routes we drive, to where we eat, and who we date. So many small, sometimes insignificant decisions were being optimized with the help of advanced data science techniques. What if we could tap into that same technology to solve some of society’s most pressing problems?

Today, four years later, that vision is becoming a reality. I’m excited to announce that Nimble has partnered with researchers Aaron Sojourner and Elton Mykerezi at the University of Minnesota, with advising from Dan Goldhaber at the University of Washington, to apply predictive modeling to one of the most important challenges we face in education — identifying and hiring amazing teachers!

In 2019, Sojourner and Mykerezi co-authored a groundbreaking study of teacher applicants to Minneapolis Public Schools. They found that by leveraging machine learning to index applicant work history data and reasons for leaving prior positions, they could predict — quite accurately — which applicants would become high performing teachers, as well as those likely to be retained over time.

And what’s even more exciting is that in addition to optimizing for these outcomes, their model also reduced human bias in the screening process, keeping the candidate pipeline more racially diverse.

Dan Goldhaber is the Director of the Center for Education Data & Research (CEDR) at the University of Washington. His research with Spokane Public Schools has identified several rating areas in the teacher screening process that are predictive of classroom effectiveness.

One of the most interesting parts about both of these bodies of research is that rather than requiring candidates to fill out long diagnostics, they simply leverage data already collected in the hiring process, allowing districts to make smarter hires while maintaining simple and streamlined applications.

Nimble is thrilled to collaborate with these amazing advisors to build proven predictive tools directly into our applicant tracking interface. Throughout this year, we'll expand Nimble’s predictive analytics function based on their research, so that we can use these insights to highlight the highest-potential talent for our district partners beginning in the 2020-2021 hiring season.

Ultimately, this will be a game changer for the Nimble product and our customers — saving time for HR and hiring managers, making hiring processes more efficient, and boosting teacher quality, retention and diversity!

If you’re interested in how your organization might benefit from this work reach out to us to learn more.

Lauren Dachille
Founder & CEO @ Nimble