13. Analysis of the High School Longitudinal Study to Evaluate Associations Among Mathematics Achievement, Mentorship and Student Participation in STEM Programs

Advancements in science, technology, and medicine have contributed to the economic growth of the United States. However, this requires individuals to be trained for careers in biostatistics, bioinformatics and other areas of science, technology, engineering, and mathematics (STEM). Despite efforts to improve student recruitment and retention in STEM fields, the proportion of STEM graduates at the undergraduate level remains low in the United States, and is the lowest among underrepresented minorities. Several initiatives by the National Science Foundation (NSF), American Statistical Association (ASA), and academic organizations have invested in training individuals by developing programs to address issues that may be contributing to low recruitment and retention rates. Some factors may include lack of mentoring received from parents and teachers on STEM careers and less opportunities to explore STEM career options. In this study, a subsample of the High School Longitudinal Study (2009–2013) dataset (HSLS:09) is analyzed. Regression models were applied to evaluate mathematics achievement and student enrollment in STEM major/careers based on their individual participation in STEM activities and mentorship. Differences based on sex, race/ethnicity, and socioeconomic status (SES) were investigated. In summary, the aim of this work was to assess the significance of these stated factors in order to give insight into STEM education policy efforts. Our hope is that this work would shed light on the roles of mentors and student participation in STEM activities to motivate future programs aimed to recruit and retain STEM students.