The U.S. population and workforce is becoming increasingly diverse; however, the STEM workforce remains primarily white, Asian, and male. This lack of diversity can create bias in the way products are developed, which in turn can perpetuate gender and racial disparities. Underrepresented (UR) students entering UW show similar rates of interest in the STEM fields as their non-UR peers, but proportionally fewer UR students and non-UR women obtain STEM degrees. Our work aims to address this discrepancy. We have developed a dashboard that enables advisers to identify those URM STEM that may be at risk of experiencing a challenging quarter. The predictive model draws from a variety of data sources to estimate when a UR STEM student is at risk of dropping out, helping their advisors provide timely, personalized support to help URM students achieve their academic and career goals.
Last updated: November 18, 2021