To better describe individual behavior within a system, this paper uses a sample of longitudinal test scores from a large urban school system to consider hierarchical Bayes estimation of a multilevel linear regression model in which each individual regression slope of test score on time switches at some unknown point in time, "kj." Preliminary evidence based on a sample of 58 elementary schools in Chicago, Illinois, suggests that change points in test score trends indeed differ from school to school. In addition the estimated posterior distribution of the change points suggests that, while the estimated timings of change in performance do not contradict the claim that a well-publicized intervention at time "t" may have been a contributive factor, changes have not been uniformly positive and do require further scrutiny. Additional results are explored using models that accommodate case weights and shorter time series. (Contains 8 figures, 3 tables, and 35 references.) (SLD)