Investing in Human Capital Underrepresented Racial Minorities Intentions

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Investing in Human Capital Underrepresented Racial Minorities’ Intentions to Attend Graduate School in STEM

Investing in Human Capital Underrepresented Racial Minorities’ Intentions to Attend Graduate School in STEM Fields Kevin Eagan Christopher Newman University of California, Los Angeles

Background • Blacks and Latinos combined representation among graduate students – 9. 5% Biological

Background • Blacks and Latinos combined representation among graduate students – 9. 5% Biological sciences – 6. 5% Physical Sciences – 6. 7% Engineering – 7% Mathematics (National Science Foundation, 2009)

Prior Research • • • Academic success in undergraduate education Selectivity and institutional control

Prior Research • • • Academic success in undergraduate education Selectivity and institutional control Socio-Economic Status Undergraduate debt Undergraduate research

Theoretical Framework • STEM Identity (Carlone & Johnson, 2007) – Performance, recognition, and competence

Theoretical Framework • STEM Identity (Carlone & Johnson, 2007) – Performance, recognition, and competence – Non-financial psycho-social motivations • Investing in human capital (Paulsen, 2001) – Direct cost, forgone earnings, returns on investment – SES and social capital

Research Questions • What effects do URM STEM students’ college experiences, accumulated loan debt,

Research Questions • What effects do URM STEM students’ college experiences, accumulated loan debt, and STEM identity have on their decision to enroll in graduate or professional school? • How do the contextual effects of higher education institutions affect STEM students’ decision to enroll in graduate or professional school immediately following the completion of their bachelor’s degree?

Methods: Data & Variables • Data: Sample from the 2004 CIRP Freshman Survey and

Methods: Data & Variables • Data: Sample from the 2004 CIRP Freshman Survey and 2008 College Senior Survey • Dependent variable: Intention to enroll in graduate/professional school by fall 2008 • Independent variables – Background characteristics – Goals at college entry – Financial considerations, including debt – College experiences – Institutional characteristics

Methods: Analyses and Limitations • Analyses – Missing data – Hierarchical generalized linear modeling

Methods: Analyses and Limitations • Analyses – Missing data – Hierarchical generalized linear modeling • Limitations – Secondary data – Restrictive dependent variable – Low survey response rate – Selection bias

Findings: Students Positive Predictors • • • Socioeconomic status Research with faculty STEM identity

Findings: Students Positive Predictors • • • Socioeconomic status Research with faculty STEM identity College GPA Major: Physical sciences Negative Predictors • Cumulative undergraduate debt • Amount of personal funds used to pay for final year of college • Major: Health sciences • Entry goal: Make more money

Findings: Institutions • Positive predictors: – Attending an HBCU – Attending a private college

Findings: Institutions • Positive predictors: – Attending an HBCU – Attending a private college or university • Explained variance across institutions: 62%

Discussion • Negative association between cumulative debt and graduate enrollment intentions • Role of

Discussion • Negative association between cumulative debt and graduate enrollment intentions • Role of undergraduate research • Positive association between STEM identity and graduate enrollment intentions • Academic major • Institutional contexts

Conclusions and Implications • Recent changes in student loan policy • Pending changes to

Conclusions and Implications • Recent changes in student loan policy • Pending changes to undergraduate research funding – Federal government – Institutions • Directions for future research

Acknowledgments This study was made possible by the support of the National Institute of

Acknowledgments This study was made possible by the support of the National Institute of General Medical Sciences, NIH Grant Numbers 1 R 01 GMO 71968 -01 and R 01 GMO 71968 -05 as well as the National Science Foundation, NSF Grant Number 0757076. This independent research and the views expressed here do not indicate endorsement by the sponsors. Contact: Kevin Eagan [email protected] com Christopher Newman Christopher. [email protected] edu Web Site: www. heri. ucla. edu/nih