Report on the Stability of Student Growth Percentile (SGP) “Value-Added” Estimates
The Student Growth Percentiles (SGPs) model, which is loosely defined by value-added model (VAM) purists as a VAM, uses students’ level(s) of past performance to determine students’ normative growth over time, as compared to his/her peers. “SGPs describe the relative location of a student’s current score compared to the current scores of students with similar score histories” (Castellano & Ho, p. 89). Students are compared to themselves (i.e., students serve as their own controls) over time; therefore, the need to control for other variables (e.g., student demographics) is less necessary, although this is of debate. Nonetheless, the SGP model was developed as a “better” alternative to existing models, with the goal of providing clearer, more accessible, and more understandable results to both internal and external education stakeholders and consumers. For more information about the SGP please see prior posts here and here. See also an original source about the SGP here.
Related, in a study released last week, WestEd researchers conducted an “Analysis of the stability of teacher-level growth scores [derived] from the student growth percentile [SGP] model” in one, large school district in Nevada (n=370 teachers). The key finding they present is that “half or more of the variance in teacher scores from the [SGP] model is due to random or otherwise unstable sources rather than to reliable information that could predict future performance. Even when derived by averaging several years of teacher scores, effectiveness estimates are unlikely to provide a level of reliability desired in scores used for high-stakes decisions, such as tenure or dismissal. Thus, states may want to be cautious in using student growth percentile [SGP] scores for teacher evaluation.”
Most importantly, the evidence in this study should make us (continue to) question the Report on the Stability of Student Growth Percentile (SGP) “Value-Added” Estimates | VAMboozled!:
