American Educational Research Association Annual Conference: 2004

1. Examining Academic Success in Undergraduate School for Students of Color: The Relative Contributions of Context, Preparation, Personal, Social, and Material Capital American Educational Research Association Annual Conference: 2004

2. About GMS • Awards 1,000 new scholarships to entering freshmen • Last dollar scholarship award • Renewable through graduate school in math, science, engineering, library science, & education • Award period–up to 5 years undergraduate & 4 years graduate

3. Eligibility Criteria • African American, American Indian/Alaska Native, Asian Pacific Islander American, or Hispanic American • Federal Pell Grant eligible • Citizen/legal permanent resident or national of U.S. • 3.3 GPA • Demonstrated leadership abilities • Community service • Extracurricular activities

4. Selection Criteria • GPA & rigorous course of study • Qualitative • Demonstrated leadership potential • Overcoming hardship or unusual circumstances • Motivation; tenacity and initiative • Intellectual curiosity and creative achievement • Demonstrated concern for others & community • Evidence of selection by, or influence on, peers • Goal setting • Persistence and potential for success in degree completion

5. Scholar Profile

6. General Program Data 1st year scholarships awarded: 4,053 Students served 2000 to 2003: 7,050 College graduates to date: 1,733 Dollars invested: $50 million/year for 20 years Nominees drawn from: U.S. & U.S. Territories Institutions of higher education: 932 institutions

7. I Know I Can! I Know I Can! Comparing High School Context, Academic Preparation and the College Choice Process Among Gates Millennium Scholarship Recipients and Non-recipients Walter Allen Marguerite Bonous- Hammarth & Susan Suh University of California, Los Angeles

8. I Know I Can! I Know I Can!The High School Contexts, Academic Preparation and the College Choice Process Among GMS RecipientsWalter R. Allen & Evellyn ElizondoUniversity of California, Los AngelesAmerican Educational Research AssociationApril 12-16, 2004San Diego, California“And you know, don’t be afraid of what other people say to you….If you think you can do it, go ahead and just do it.” (Native American Female)

9. Research Questions • What school contexts negatively influence students' academic preparation? • What school contexts positively influence students' academic preparation? • What general trends were found in students’ college process and transition?

10. Negative School Contexts: Biased Distribution of Resources Between AP and Non-AP Students “You have kinda like the smart kids and the like not so smart kids. And when I was in [high] school, all the kids who were in the good classes [AP], they got the benefits of everything. We got college tours, mentors, tutoring, and like help with our financial aid package. But as far as the other kids, they didn't get any help toward preparing for college, and that's why the majority of them don't even attend college after graduating [high school].” (Asian Female) “Like if you were average just like, ‘Okay, you can go to college.’ But if you were a superstar they really, really pushed you.” (Black Female) “I think for like my school like, ’cause I was smart, you know, I was given all the resources. But like somebody that's average, you know, well, whatever they wanna do, military, nothing else, you know? They didn't really get any help.” (Black Male) “A lot of Hispanics were illegal residents, they weren't getting the same sort of info. And, so that basically kept us down from receiving a lot of help. I wasn't allowed to be in a… we had no AP classes. We had nothing whatsoever. And so basically, everything that I had to do was basically, you know, do it all myself.” (Latino)

11. Negative School Contexts: Scarce Resources, Limited Scholarship Awareness, and Low Student Expectations “Where I graduated from, we didn't have any resources and they didn't give us an opportunity for scholarships. They didn't know anything. They didn't know about this GMS thing, and I had to beg them to nominate me so I could go [and apply].” (Asian Female) “As far as [college] applications and scholarships, looking for scholarships, I had to do a lot of it on my own.” (Black Female) “Yeah, the counselor was there but, you know...he had two jobs because they couldn’t afford just to pay [him as] a counselor. It's like every staff had more than one role to fill so it made it kind of hard.” (Black Male) “I talked to her [counselor] about [the GMS scholarship] and she was like, I really would count on it, getting the scholarship, and you know, going to that college…I kinda did a lot of things on my own like, I applied for scholarships. And you know, my dream college, hey, I got in.” (Native American Female)

12. Positive School Contexts: Centralized College Information & Strong Commitment to Student Success “They [the high school] had a big Post-Graduate Center available for kids to go whenever. And around the time for college applications they always made the staff available, they always had different colleges coming in to meet with kids. So they did a really good job just influencing you to go and get those resources to go to college." (Latina) “We had our Career Center which has every single catalogue, university, you know, catalogue in it…And once you go and look, you keep going back. And so that was like the one thing that got me really interested in knowing that is all there for anybody, any resource there.” (Native American Female) “Any time you needed information, she [counselor] was there. If you wanted to know about a specific college, she'll have a huge folder with your name on it. She did little things that like just made you really, really just say, ‘Hey, I can do this, I can go to college,’ and she's like making this happen for me.” (Black Female)

13. Origins of College Aspirations: Upward Mobility, Negative Parent Role Models, & College as a Natural Progression “I didn’t want to work 16 hours a days, you know, all during the summer…Coming home from the fields with cut fingers, bleeding and stuff. I figured I needed to do something else.” (Latino Male) “My mother, she really didn‘t go to college or anything like that. So I decided that I wanted to take the initiative to go to college on my own and be successful.” (Black Female) “I could see how my parents have to work really hard. My dad did construction work…even though he’s working like a lot harder than other people, he don’t make much money.” (Black Male) “It was never in my brain not to consider college. It was just like, that’s me, I’m going to college.” (Black Female) “It’s like a natural progression, you don’t even…I didn’t even think about not going to college.” (Black Male)

14. College Selection: Campus Visits Made All the Difference “I had to choose between three colleges, and I had to go fly out to all of them first before I made a decision.” (Female) “They were offering a visitation program so I flew out there to visit the campus. And I just fell in love with it.” (Native American Female) “I don’t know how they [parents] found the money for me to go and look at the colleges one more time so I could make sure [about] my final decision ’cause they wanted to make sure I would be completely happy with what I decided.” (Latina Female)

15. Implications • Equal access to college preparation and resources is essential for all students • Institutional commitment to student success matters • Cultural brokers are paramount to college access • Campus visits are an essential component in the college process • Greater outreach funding is needed to increase students’ awareness and exposure of college life

16. Correlates of Academic Success of Gates Millennium Scholars William E. Sedlacek wsed@umd.edu Hung- Bin Sheu University of Maryland

17. Research Questions • Do the selection variables correlate with student success? • What are the academic behaviors of Scholars?

18. Noncognitive Variables • Scholars selected with noncognitive variables (alpha = .92) • Self- Concept • Realistic Self- Appraisal • Navigating System/Racism • Long- Range Goals • Leadership • Strong Support Person • Community • Nontraditional Learning

19. Noncognitive Variable Results • Self-Concept, Realistic Self-Appraisal, Navigating System, and Community were positively correlated with GPA (.05) • Community was positively predictive of academic engagement (.0001) • Self-Concept was negatively predictive of difficulty keeping up with schoolwork (.01) • Realistic Self-Appraisal positively predicted hours studied per week (.05)

20. Scholars & Non-Scholars • 95% of Scholars indicated that they were very unlikely to drop out of school and were committed to earn a degree at their current institution. • Among African Americans, significantly more Scholars (97%) than Non-Scholars (94%) felt they were unlikely to drop out of school. A similar response was also observed for American Indians (94% for Scholars versus 87% for Non-Scholars). • 90% of Scholars expected to complete a master’s degree or above. African American Scholars had higher educational aspirations than African American Non-Scholars. Among female Scholars, African Americans had higher educational aspirations than American Indians and Asian/Pacific Islanders. • Among Scholars, Asian/Pacific Americans tended to spend more time studying per week (27.58 hrs) than American Indians (17.89 hrs). On the other hand, among Asian/Pacific Islanders, Scholars (27.58) spent more time than Non-Scholars (23.22 hrs) studying per week.

21. Conclusions • Noncognitive variable scores show reliability and validity in predicting success • Scholars show academic behaviors that will correlate with their later success in school • High educational aspirations • Unlikely to drop out • Committed to earning a degree at current school

22. References • Sedlacek, W. E. (2004). Beyond the big test:Noncognitive assessment in higher education. San Francisco: Jossey-Bass. • Sedlacek, W. E. & Sheu, H. B. (in press). Academic success of Gates Millennium Scholars. Readings on Equal Education.

23. The Diamond in the Rough: Overcoming the Lack of Human, Social, andCultural Capital Sylvia Hurtado University of California, Los Angeles AERA, San Diego, 2004

24. Access Issue • UCLA CIRP data show that high income students with 1300+ SATs and A+ averages are almost twice as likely as low income students with the same credentials to attend the most selective colleges. Why? • First generation status • Poor counseling in high schools • Lack of knowledge about the differences between colleges • “Sticker Shock” prevents students from the lowest income categories from applying to elite colleges

25. Are There Diamonds in the Rough? • Bright, low income kids who overcompensate for bad schools (extra courses, summer programs, etc.) • Bright, low income kids who don’t know they are qualified to attend the best colleges • Bright, low income kids who demonstrate unusual leadership potential

26. Identifying These Students Admissions officer visits to predominantly minority high schools or “non-feeder” high schools, all other search techniques rely on SAT scores Gates Millennium Scholars program systematically identifies these students through: • Scholarship attracts the “Diamonds in the Rough” • Criteria noncognitive and leadership qualities, rather than SAT (which is income dependent) • Connections between high schools and minority-serving organizations

27. Transition from “Diamond in the Rough” to Successful College Student Figure 1 Scholarship Aid • Increased time devoted to: • Studying • Peer networks • Using college resources • Seeking opportunities for engagement Academic Success Positioning for employment Choice of graduate opportunities

28. Future Research • Examining the long term effects of the Gates Millennium Scholars Program • Comparing the progress of the lowest income students with other students • Comparing Gates Millennium Scholars with other low income students—does scholarship aid have the same impact on other students? • Finding new ways to identify the Diamond in the Rough and assisting him/her to college success

29. The Nexus Between Finances and Student Involvement in College Persistence Edward P. St. John Indiana University

30. Research Questions • Both involvement and finances have been offered as explanations for differentials in persistence rates • The relationship between the two forces has seldom been examined • The NORC surveys provided an opportunity to consider the questions: • How do finances influence involvement by low-income, high achieving students? • Do both finances and involvement influence persistence?

31. Methods • This study used the NORC surveys for 2000 freshman students • The analyses considered • The impact of financial aid on involvement (social and academic), controlling for background and financial reasons for choice • The impact of finances and involvement on persistence, controlling for other factors • The analyses used logistic regression models

32. Findings on Involvement in Cultural Groups • Involvement in cultural groups positively associated with: • Receiving GMS awards • Choosing colleges because of low costs • Choosing colleges because of scholarships and grants • Choosing colleges because of strong reputations • Being African American (compared to Asian American)

33. Findings on Involvement in Community Service Activity • Males were less likely to be involved in community service • Involvement in community service activities positively associated with: • Choosing a school because of grant or scholarship • Choosing a school because of strong reputation

34. Support by Faculty (Indicator of Academic Involvement) • Males were less likely to feel supported by faculty • Students in other race/ethnic groups were more likely than Asian Americans to feel supported by one or more faculty • Choosing a college because of a grant or scholarship was positively associated with support by faculty • Choosing a school because it was close to home was negatively associated with this outcome

35. Involvement in a Faculty Research • Variables positively associated with involvement in faculty research: • Choosing a college because of its reputation • Attending a private college (compared to public four-year) • Amount of scholarship • Variables that reduced the odds: • African Americans and American Indians (compared to Asians) • Attending a two-year college

36. Findings on Persistence (Maintained Continuous Enrollment) • Scholarship grant amount positively associated with persistence (as was GMS before considering aid amounts) • Involvement in community groups negatively associated with persistence • Other involvement variables were not significant in persistence

37. Conclusions • Do both finances and involvement influence persistence? • Finances exerted a more substantial direct influence • How do finances influence involvement by low-income, high-achieving students? • Finances influenced involvement through perceptions (choosing colleges because of scholarships & low costs), scholarship amounts, and GMS (independent of scholarship amounts)

38. Implications • GMS has a positive influence on involvement in college, as well as on persistence • The decline in the purchasing power of government need-based grants reduce opportunities for involvement as well as for persistence.

39. Shaping Access and Participation: Exploring the Implications of the Gates Millennium Scholarship William Trent University of Illinois at Urbana-Champaign

40. GMS and First College Type (level, control, minority status, and selectivity) • GMS recipients were significantly less likely to attend 2-year institutions than non-recipients (3.6% vs. 7.7%). • GMS recipients were significantly more likely to attend private institutions than non-recipients (43.1% vs. 29.1%). • There is a marginally significant difference in the likelihood of attending an MSI. GMS recipients were slightly less likely to attend an MSI than were non-recipients (17.4% vs. 20.3%, P = 0.051). • On average, GMS recipients attend more selective institutions compared to non-recipients (acceptance rate is: 58.4 vs. 63.1) and this difference is statistically significant.

41. GMS and Change of College Choice • Overall, about 15% of all GMS applicants indicated that they changed their college choice based on whether or not they received the scholarship. • A significantly higher percentage of African American, Native American and Asian American applicants indicated change of choice compared to Hispanic applicants (15.5%, 17.4%, 19.9%, and 8.2% respectively). • A significantly higher percentage of females indicated change of choice compared to males (16.2%, 12.0%). • A significantly higher percentage of GMS Non-recipients indicated change of choice than recipients (17.9%, 6.0%). The same pattern still holds true after controlling for gender. • Among African American, Native American and Asian American, applicants a significantly higher percentage of GMS Non-recipients indicated change of choice than recipients, but the difference among Hispanic among is not statistically significant.

42. My GMS assistance was critical to attending current college • 43.7% of GMS recipients strongly agree with the above statement, and 36.3% agree. Overall, 4 in 5 recipients believe agree GMS is critical to attend their current college.

43. GMS and STEM • GMS recipients are slightly less likely to be in STEM majors (51.0% vs. 55.6%) than non-recipients. • Within each racial group, GMS recipients are slightly less likely to be in STEM, but none of these differences reaches statistical significance.

44. STEM and Gender • Males are significantly more likely to be in STEM majors than females (63.4% vs. 50.7%) • African American males are significantly more likely to be in STEM majors than females counterparts (64.9% vs. 51.8%) • Native American males are significantly more likely to be in STEM majors than females counterparts (58.3% vs. 44.4%) • Asian American males are significantly more likely to be in STEM majors than females counterparts (69.6% vs. 60.6%) • Hispanic American males are significantly more likely to be in STEM majors than females counterparts (56.6% vs. 40.4%)

45. STEM and First College/University Type • GMS applicants who enrolled in HBCUs, HSIs, and Tribal institutions are significantly more likely to be in STEM majors than those in TWIs (66.5%, 56.5%, 71.6%, and 52.9% respectively). • GMS applicants who attended public institutions are more likely to be in STEM than those who attend private institutions (58.6%, 44.8%). • GMS applicants who attended MSIs are significantly more likely to be in STEM than those who attended Non-MSIs (57.8%, 53.2%). • GMS applicants who were in 2-year institutions are more likely to be in STEM than those in 4-year institutions (61.8%, 53.8%).

46. Selected Regression results: Major choice (STEM vs. Non-STEM) • After controlling for other variables, Gates status is not a significant predictor for STEM. • Percentage of African American and Hispanic Enrollment in high school is positively associated with the odds of majoring in STEM. • The odds of majoring in STEM for male is significantly higher than that for female. • The odds of majoring in STEM for African American, Hispanic, and Native American is significantly smaller than that for Asian Americans.

47. Selected Regression results: First College Selectivity (Acceptance Rate) • All other things being the same (race, gender, parents’ education, high school racial composition, # of AP courses offered by high school, ACT test score), Gates recipients attended more selective colleges than non-recipients (p < 0.10). • Comparing to Asian American, and controlling for all other variables mentioned above, Native Americans attended less selective school. Hispanic and African Americans do not significantly differ from Asian American in the college selectivity index. • High school characteristics such as number of AP course offered and the percentage of African American and Hispanic students in the school are significantly associated with the selectivity of college. Students from schools that offer more AP courses and schools that have higher percentage of African American and Hispanic students attended more selective colleges, after controlling for individual race/ethnicity, gender, parents’ education, test score and even GMS status. • After controlling for all variables mentioned above, whether a respondent is in STEM or not does not help much in predicting the selectivity of the colleges attended.

48. STEM and Race • There is a significant association between race and major. Asian American are most likely to be in STEM (63.7%), followed by African American (54.9%), Native American (48.9%) and Hispanic American (45.9%).

49. Conclusions and Implications • GMS recipients are making choices influenced by the receipt of the Scholarship. • The main influence appears to be on college choice both in choosing 4-year colleges and in choosing more selective colleges. • The numbers of applicants choosing STEM fields is somewhat greater among non-recipients. This difference may be cohort specific and may be a function of GMS recipients attending TWIs and major field entry requirements.