1. 1 Assessing Scientific Inquiry and Leadership Skills (AScILS) Report to NIGMS Advisory Council January 25, 2008 Martin M. Chemers, PI University of California, Santa Cruz

2. 2 Overarching Research Questions How do activities implemented by biomedical research career support programs (especially research and mentoring) influence: –Scientific research skills –Science team leadership and membership skills –Beliefs in efficacy and collective efficacy regarding these skills –Identity as a scientist –Stage-appropriate educational and career outcomes? Are these influences similar for minority and non-minority students?

3. 3 Program Components Psychological Processes Outcomes Research Experience Community Involvement Academic Support Financial Support Mentoring: Instrumental Socio-Emotional Performance: Science Inquiry and Leadership Skills Commitment: Satisfaction and Continuation in Science Education and Research Student Demographics: Ethnicity, Gender Science Inquiry Self-Efficacy Leadership and Teamwork Self-Efficacy Identity and Belonging as a Scientist

4. 4 The Research Model Theory-Driven Interdisciplinary Multi-Method

5. 5 Brief Overview of Methods Qualitative Studies: (Assessment of Program Components) In-depth interviews (H.S., U.G., & Grad.) (Longitudinal Case Studies) Retrospective Surveys (UCSC Students; COSMOS; SACNAS) Performance Assessments (Simulations & Mentor Ratings) Longitudinal Quantitative Studies

6. 6 Today’s Report: Quantitative Survey Studies UCSC Undergraduate Retrospective Survey SACNAS Retrospective Undergraduate and Graduate/Post-Doc Surveys

7. 7 Program Components Psychological Processes Outcomes Research Experience Community Involvement Academic Support Financial Support Mentoring: Instrumental Socio-Emotional Performance: Science Inquiry and Leadership Skills Commitment: Satisfaction and Continuation in Science Education and Research Student Demographics: Ethnicity, Gender Science Inquiry Self-Efficacy Leadership and Teamwork Self-Efficacy Identity and Belonging as a Scientist

8. 8 UCSC Undergraduate Retrospective Survey Population –All 1095 participants from 14 UCSC science or engineering support programs, 1999/2000 to 2003/2004 –UCSC Science/Engineering majors not in programs during those same years Invited 100% of 870 underrepresented minorities Invited representative proportion of other ethnic groups: 548 Whites, 191 Asians, 131 Others

9. 9 UCSC Undergraduate Retrospective Survey Sample 502 (18%) completed survey 56% women Ethnic background –34% URM –23% Asian –40% White –4% Other Average age = 23.2 years

10. 10 UCSC Undergraduate Retrospective Survey Results Community Involvement Instrumental Mentoring Identity as a Scientist Science Inquiry Self- Efficacy Commitment Research Experience.42/.46.37/.60 ns/.23.24/ns Model Fit: χ 2 (15) = 8.60, p =.90, CFI = 1.0, IFI = 1.0, GFI =.99, NNFI = 1.0, RMR =.03, RMSEA =.00 (.00,.02).31/.25.11/.12.69/.79.52/.52.52/.42.29/.21.16/.15 Blue (Left) = URM students Red (Right) = White students

11. 11 SACNAS Undergraduate Retrospective Survey Sample 327 completed survey 74% Current Undergrads, 26% Recent Grads 67% women Ethnic Background –74% URM –14% Asian –11% White –1% Other Average age = 24.06 years

12. 12 SACNAS Undergraduate Retrospective Survey Results Community Involvement Instrumental Mentoring Teamwork & Leadership Self-Efficacy Identity as a Scientist Science Inquiry Self- Efficacy Commitment Research Experience.34.53.24.23.17.26.24.29.32.51.10 Model Fit: χ 2 (10) = 22.20, p =.01, CFI =.97, IFI =.97, GFI =.98, NNFI =.94, RMR =.02, RMSEA =.06 (.03,.10)

13. 13 SACNAS Graduate/Post-Doc Retrospective Survey Sample 338 completed survey 82% Current Graduate Students, 18% Post-Docs 63% women Ethnic Background –86% URM –7% Asian –6% White –1% Other Average age = 29.83 years

14. 14 SACNAS Graduate/Post-Doc Retrospective Survey Results Research Experience Community Involvement Instrumental Mentoring Teamwork & Leadership Self-Efficacy Identity as a Scientist Science Inquiry Self- Efficacy Commitment Professional Experience Socioemotional Mentoring Model Fit: χ 2 (12) = 54.42, p <.001, CFI =.96, IFI =.96, GFI =.97, NNFI =.87, RMR =.03, RMSEA =.10 (.08,.13).14.12.16.25.12.11.20.23.30.12.49.16.23

15. 15 Summary & Conclusions Identity most direct predictor of commitment and performance Science inquiry self-efficacy both indirect (through identity) and direct predictor of commitment and performance Research, mentoring, and community involvement predict science inquiry self- efficacy and identity

16. 16 Implications for Policy and Practice Scientific self-efficacy and identity are positively affected by interventions involving research and mentoring. Programs should place greater emphasis on these psychological mediators.