The most cost-effective solution K-12 HR leaders are missing
What if there were an intervention that K-12 talent and HR leaders could adopt in a matter of just a few weeks, that had a benefit to cost ratio more than four times that of the best K-12 interventions we know — including things like intensive tutoring, summer programs and class size reductions? What if this solution were shown to have a significantly greater impact on student outcomes than common strategies like performance pay programs or targeted teacher professional development — all while being cost neutral to districts? Would you try it in your district?
Recent research shows schools can significantly improve teacher performance and student outcomes through a surprising lever — improved hiring decisions from within their existing pool of teacher job applicants. The findings, which have been replicated across a variety of districts, show that status quo hiring regularly misses out on some of the strongest potential teacher applicants and that by improving teacher hiring decisions we can significantly improve teacher effectiveness and retention, hiring equity, and student outcomes.
Unfortunately, the reality is that few districts and charters have the centralized resources to implement a rigorous, labor-intensive screening and selection process. And where thorough screening processes are put into practice, they can slow down hiring or take up resources that might otherwise be used toward things like recruitment or professional development.
That’s where Nimble comes in. We’re thrilled to announce the launch of Nimble Candidate Insights or NCI — research-backed AI assistance embedded within our applicant tracking system to help K-12 hiring managers quickly identify and hire top teacher candidates.
Over the last year, we’ve partnered with leading researchers to develop this AI-based tool, to help our districts improve new hire performance and retention, while reducing bias and staff time spent in the screening process. NCI automatically flags the candidates that evidence suggests will be most effective at promoting student learning and most likely to stay with the district over time. This method predicts teacher performance and retention more effectively than typical human screening, while reducing racial bias in teacher selection.
Research shows that the impact of leveraging this predictive model on student learning would be on par with some of the most effective K-12 interventions — driving student learning gains as much as targeted teacher professional development, performance pay programs and structured tutoring, and more than twice as much as things like elementary class size reduction, and summer reading programs.
When we look at cost effectiveness, the results are even more striking. Because leveraging Nimble’s applicant tracking system with NCI is typically about cost neutral with districts’ existing systems, the ratio of student benefit to cost for this intervention is about 1,000 to 1 — making Nimble 5 to 10 times as cost effective as the best interventions we know of to improve student outcomes.
To learn more about NCI and how it can help your students and schools, reach out to us and one of our team members will be in touch!
