Total Workforce vs. STEM Workforce Demographics Sources: National Science Foundation, 2009 & U.S. Bureau of Labor Statistics, 2009.

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Presentation transcript:

Total Workforce vs. STEM Workforce Demographics Sources: National Science Foundation, 2009 & U.S. Bureau of Labor Statistics, 2009

Structural Characteristics Selectivity Institutional Control Institutional Type Percent of students majoring in STEM Contextual Influences Conceptual Model Utilizing SCCT Framework (Lent, Brown, & Hackett, 1994) Institutional Level Variables Background Contextual Affordances Socioeconomic status Parent with STEM career Concerns w/ financing college Person Inputs Gender College Experiences Studied with other students Performed community service for a class Asked a professor for advice Worked full-time while in college Joined a club/org related to major Faculty provided opportunity for research Pre-College Learning Experiences High School GPA Math + Verbal SAT Score Yrs of high school math Yrs of high school physical science Yrs of high school bio science Self-efficacy Self-rated: Academic ability Self-rated: Leadership ability Self-rated: Mathematical ability Outcome Expectations To train for career Working for social change High income potential Social recognition or status Availability of jobs Leadership potential Discovery/enhancement of knowledge Importance of promoting racial understanding Technical Interests Science Identity Goals Degree Aspirations Student Level Variables Retained STEM Career Interests Senior Year Perceptions Satisfaction w/ science & math courses Satisfaction w/ leadership opportunities Sense of belonging on this campus Campus racial tension

o Data Source o 2004 Freshman Survey (TFS) o 2008 College Senior Survey (CSS) o 2004 IPEDS institution data o Sample o 3,165 entering freshmen with STEM career plans o 218 institutions o 47% URM; 53% Non-URM o 63% female; 37% Male

Student Level Predictors Delta-P (sig) High school GPA 3.7%* Reason for enrollment: train for career 9.4%* Career concern: leadership potential -6.7%* Studied with other students 9.7%*** Joined a club related to major 10.5%** Faculty provided opportunity for research 6.7%** Satisfaction w/ science & math courses 8.6%*** *** p<0.001, ** p<0.01, * p<0.05

Institution Level Predictors Delta-P (sig) Institutional selectivity -6.1%*** Institutional control (private) 9.5%* Percent of STEM majors 3.6%* *** p<0.001, ** p<0.01, * p<0.05

Cross-sample Comparison URM Non URM Significant effects across both groups Career concern: leadership potential- * Studied with other students+ ***+ * Joined a club related to major+ **+ *** Satisfaction w/ science & math courses+ ***+ * Institutional selectivity- ***- * Percent of STEM majors+ *+ ** Significant effects for URM High school GPA+ *ns Reason for enrollment: train for career+ *ns Faculty provided opportunity for research+ **ns Institutional control (private)+ *ns Significant effects for Non-URM Socioeconomic Statusns- * Math + Verbal SATns+ * Career concern: enhancement of knowledgens+ *** Worked full-time during collegens- *** *** p<0.001, ** p<0.01, * p<0.05

Contact Information Acknowledgments: This study was made possible by the support of the National Institute of General Medical Sciences, NIH Grant Numbers 1 R01 GMO and R01 GMO as well as the National Science Foundation, NSF Grant Number This independent research and the views expressed here do not indicate endorsement by the sponsors. Papers and reports are available for download at: Project Faculty and Co-PIs: Sylvia Hurtado Mitchell Chang Monica Lin Gina Garcia Felisha Herrera Postdoctoral Scholars: Kevin Eagan Josephine Gasiewski Administrative Staff: Aaron Pearl Graduate Research Assistants: Christopher Newman Minh Tran Jessica Sharkness Cindy Mosqueda Juan Garibay Tanya Figueroa