Abstract
Improving teacher selection is an important strategy for strengthening the quality of the teacher workforce. As districts adopt commercial teacher screening tools, evidence is needed to understand these tools’ predictive validity. We examine the relationship between Frontline Education’s TeacherFit instrument and newly hired teachers’ outcomes. We find that a 1 SD increase on an index of TeacherFit scores is associated with a 0.06 SD increase in evaluation scores. However, we also find evidence that teachers with higher TeacherFit scores are more likely to leave their hiring schools the following year. Our results suggest that TeacherFit is not necessarily a substitute for more rigorous screening processes that are conducted by human resources officials, such as those documented in recent studies.
Matthew Lenard
PhD candidate in Education Policy & Program Evaluation
I am a Ph.D. candidate at the Harvard Graduate School of Education (HGSE) in its Education Policy and Program Evaluation concentration. My research centers on using causal inference research designs to measure the impacts of education programs and policies. I typically study topics at the intersection of education and economics, but also draw from the traditions of sociology and political science. My current projects focus on career and technical education, peer effects, school choice, and teacher labor markets.