EAGER: The Use of Institutional Data to Identify Predictors of STEM Degree Completion

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Abstract: Hispanics are now the largest minority group enrolling at four-year colleges and universities; however, degree completion rates remain lower than among non-Hispanic White and Asian Americans. Student persistence and success in pursuit of undergraduate degrees in science, technology, engineering and mathematics (STEM) fields are not well-predicted simply by prior academic preparation and test scores, and furthermore, those experiences or qualities which enhance retention may differ both across racial or ethnic groups, and across disciplines. This study develops highly detailed institutional data from a large Hispanic-Serving public university with a substantial population of historically underrepresented minorities. These data have potential to detect possible differences by race/ethnicity in the relative importance of various factors in student intentions, retention, and completion of STEM degree programs.This pilot project explores the potential for using existing, large-scale institutional data at the university level to identify factors that may contribute to greater participation of underrepresented minorities in STEM fields. Large-scale analytic datasets including such diverse data on pre-college preparation, financial aid, course enrollments and completions, and demographics of students and faculty are rare. This project will extract, combine, and recode student- and course-related information from multiple data sources to produce new longitudinal, student-level analytic data files, permitting examination of how student characteristics, course preparation and sequencing, and instructional environments interact to facilitate STEM degree completion. Exploratory descriptive analyses utilizing the new analytic files will assess feasibility and appropriateness of applying more sophisticated econometric modeling and simulation-based approaches, towards identifying and evaluating policy interventions to increase participation of underrepresented minorities in the STEM workforce.