Evidence of grade and subject-level bias in value-added measures

While value-added models (VAMs)—the statistical tools used to measure teacher effects on student achievement scores—continue to emerge throughout districts and states across the country, education scholars simultaneously recommend caution, especially in terms of the inferences that are made and/or used based on VAM outcomes. This research note investigates an unexplored feature of bias in VAM-based estimates—that which is associated with grade levels and subject areas. Findings contribute an alternative perspective regarding how we think about VAM-based bias and teacher classifications.