Considerable theory regarding how employers learn about worker productivity remains untested. Examining the provision of objective estimates of teacher performance to school principals, we establish several facts supporting a simple Bayesian learning model with imperfect information. First, the correlation between performance estimates and prior beliefs rises with more precise objective estimates and more precise subjective priors. Second, new information exerts greater influence on posterior beliefs when it is more precise and when priors are less precise. Employer learning also affects job separation and productivity in schools, increasing turnover for teachers with low performance estimates and producing small test score improvements.