  Creating equitable performance outcomes among students is a focus of many
instructors and researchers. One focus of this effort is examining disparities
in physics student performance across genders, which is a well-established
problem. Another less common focus is disparities across racial and ethnic
groups, which may have received less attention due to low representation rates
making it difficult to identify gaps in their performance. In this
investigation we examined associations between Learning Assistant (LA)
supported courses and improved equity in student performance. We built
Hierarchical Linear Models of student performance to investigate how
performance differed by gender and by race/ethnicity and how LAs may have
moderated those differences. Data for the analysis came from pre-post concept
inventories in introductory mechanics courses collected through the Learning
About STEM Student Outcomes (LASSO) platform. Our models show that gaps in
performance across genders and races/ethnicities were similar in size and
increased from pre to post instruction. LA-support is meaningfully and reliably
associated with improvement in overall student performance but not with shifts
in within-course performance gaps.
