Transcript Examining Academic Succes in Undergraduate School for

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
About GMS
 Awards
 Last
1,000 new scholarships to entering freshmen
dollar scholarship award
 Renewable
through graduate school in math, science,
engineering, library science, & education
 Award
period–up to 5 years undergraduate & 4 years
graduate
Eligibility Criteria
 African
American, American Indian/Alaska Native, Asian
Pacific Islander American, or Hispanic American
 Federal
Pell Grant eligible
 Citizen/legal
 3.3

permanent resident or national of U.S.
GPA
Demonstrated leadership abilities

Community service

Extracurricular activities
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
Scholar Profile
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:
institutions
932
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
I Know I Can! I Know I Can!
The High School Contexts, Academic
Preparation and the College Choice
Process Among GMS Recipients
Walter R. Allen & Evellyn Elizondo
University of California, Los Angeles
American Educational Research Association
April 12-16, 2004
San 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)
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?
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)
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)
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)
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)
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)
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
Correlates of Academic
Success of Gates
Millennium Scholars
William E. Sedlacek
[email protected]
Hung- Bin Sheu
University of Maryland
Research Questions

Do the selection variables correlate with student
success?

What are the academic behaviors of Scholars?
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
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)
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.
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
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.
The Diamond in the Rough: Overcoming the
Lack of Human, Social, and Cultural Capital
Sylvia Hurtado
University of California, Los Angeles
AERA, San Diego, 2004
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
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
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 minorityserving organizations
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
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
The Nexus Between Finances and Student
Involvement in College Persistence
Edward P. St. John
Indiana University
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 lowincome, high achieving students?

Do both finances and involvement influence
persistence?
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
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)
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
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
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
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
Conclusions

Do both finances and involvement influence
persistence?
 Finances exerted a more substantial direct
influence

How do finances influence involvement by lowincome, high-achieving students?
 Finances influenced involvement through
perceptions (choosing colleges because of
scholarships & low costs), scholarship amounts,
and GMS (independent of scholarship amounts)
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.
Shaping Access and Participation:
Exploring the Implications of the
Gates Millennium Scholarship
William Trent
University of Illinois at Urbana-Champaign
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 nonrecipients (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.
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.
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.
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.
STEM and Gender

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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%)
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%).
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.
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.
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%).
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.