Success and Attrition Factors for High Achieving Underrepresented/ Underserved Students
Barry Nagle, GMS/UNCF Senior Research AssociateJin Liu, Research Analyst
National Scholarship Providers Association Annual ConferencePittsburgh, PAOctober 2014
2
Background: GMS Program
The Gates Millennium Scholars (GMS) program, established in 1999, is a 1.6 billion dollar initiative funded by grant from the Bill & Melinda Gates Foundation.
The goal of GMS is to promote academic excellence and to provide an opportunity for 20,000 outstanding students with significant financial need to reach their full potential.
3
Background: Program Partners
• UNCF- the United Negro College Fund is the administrator of the GMS initiative and has partnered with the following organizations:
• Asian & Pacific Islander American Scholarship Fund
• American Indian Graduate Center Scholars
• Hispanic Scholarship Fund
4
Topics
• Success/Attrition Factors Demographic Characteristics Institution Characteristics Student Education Characteristics
High School GPA Nomination Composite Scores STEM Major Status Deferment
• In Development: Engagement• Applying the Knowledge• Discussion
5
Study Purpose
• Identify students potentially at-risk of not attaining graduation
6
Success Factors:Demographics
7
Demographics: Cohort
• Overall graduation rates are approximately 90% (Scholars in Cohorts 1-8)
91.5% 89.6% 91.3% 89.8% 90.7% 89.9% 90.4% 91.0% 90.7%
0%
25%
50%
75%
100%
Cohort 1 Cohort 2 Cohort 3 Cohort 4 Cohort 5 Cohort 6 Cohort 7 Cohort 8 Overall
Per
cen
tag
e
Cohort
8
Demographics: Gender
• Females earn an undergraduate degree at higher rates than males
• Females have a 91% graduation rate. Males have a 89% graduation rate. X2= 18.8366, df=1, p<.000
90.7%
89.3%
91.4%
0% 25% 50% 75% 100%
Total
Males
Females
Percentage
Gen
der
9
Demographics: Primary Ethnicity
• Three Primary Ethnicity groups have graduation rates of 90% or more (X2= 576.0241, df=3, p<.000)• African American: 93.4%• American Indian: 72.0%• Asian & Pacific Islander: 95.8%• Hispanic American: 92.5%
90.7%
92.5%
95.8%
72.0%
93.4%
0% 25% 50% 75% 100%
Total
Hispanic American
Asian & Pacific Islander
American Indian
African-American
Percentage
Pri
mar
y E
thn
icit
y
10
Demographics: Gender and Primary Ethnicity
• For every ethnicity, females have higher graduation rates than males (X2= 595.1700, df=7, p<.000). Female-Male differences:• African American: 3.3%• American Indian: 2.9%• Asian & Pacific Islander: 0.4%• Hispanic American: 2.1%
94.4%
72.9%
96.4%92.6% 91.4%91.1%
70.0%
94.4% 92.2% 89.3%
0%
25%
50%
75%
100%
African-American American Indian Asian & PacificIslander
HispanicAmerican
Total
Females Males
11
Demographics: Other
Graduation Rates for Students with Known Status
• First-generation college students• First-Generation: 90.2%• Non First-Generation: 89.5%
• Dependency Status• Dependent: 90.6%• Independent: 87.1%
12
Success Factors:Institution Characteristics
13
Institution Characteristics: Top Graduation Rates
Top Ten by Graduation Rate/50 Students or More
Earned Degree
TotalGraduation
Rate
Spelman College 66 67 98.5%
Duke University 63 64 98.4%
Stanford University 173 176 98.3%
University of Southern California 99 101 98.0%
Georgetown University 49 50 98.0%
Harvard University 136 139 97.8%
University of Pennsylvania 70 72 97.2%
Columbia University in the City of New York 60 62 96.8%
Brown University 75 78 96.2%
Cornell University 97 101 96.0%
14
Institution Characteristics: Private vs. Public
• Scholars that attend private institutions graduate at higher rates than Scholars that attend public institutions
• Private school attendees have a 93.9% graduation rate compared to the public school attendee graduation rate of 89.3% (X2= 81.2958, df=1, p<.000)
90.7%
93.9%
89.3%
0% 25% 50% 75% 100%
Total
Private
Public
Percentage
Inst
itu
tio
n T
ype
15
Institution Characteristics: Private/Public and Gender• Females and males that attend private institutions graduate at
higher rates than Scholars that attend public institutions (X2= 105.8424, df=3, p<.000)
94.6%
92.7%
90.1%
87.5%
0% 25% 50% 75% 100%
Private: Females
Private: Males
Public: Females
Public: Males
Percentage
Inst
itu
tio
n T
ype
16
Institution Characteristics: Private/Public and Primary Ethnicity• Scholars that attend private institutions in all PE groups have
greater graduation rates than public school attendees (X2= 618.804, df=7, p<.000). Private-Public differences:• African American: 1.8%• American Indian: 6.1%• Asian & Pacific Islander: 0.9%• Hispanic American: 4.8%
92.8%
72.3%
95.5%90.8% 89.3%
94.6%
78.4%
96.4% 95.6% 93.9%
0%
25%
50%
75%
100%
African American American Indian Asian & PacificIslander
HispanicAmerican
Overall
Public Private
17
Institution Characteristics: Private/Public, Gender and Primary Ethnicity• For all primary ethnicities, females and males that attend private
institutions have higher graduation rates than Scholars that attend public institutions (X2= 642.6317, df=15, p<.000).
• AA, AP, and HA Scholars that attend private institutions have graduation rates of 90% or higher
• AI Scholars that attend private institutions have graduation rates of 70% or higher
18
Success Factors:Student Education Characteristics
19
Student Characteristics: High School GPA
• Scholars that earn a degree have higher High School GPAs than Scholars that do not earn a degree
• Degree earners have a 3.77 mean HS GPA compared to 3.70 for non-degree earners (t= 11.3729, df=924.425, p<.000)
3.68
3.77
0 1 2 3 4
No Degree Group
Earned Degree Group
High School GPA
20
Student Characteristics: High School GPA by Gender• Female and male Scholars that earn a degree have higher High
School GPAs than female and male Scholars that do not earn a degree, respectively (F=48.55, df=3, p<.000)
• Significant TukeyHSD contrasts:• Female Earned Degree HS GPA (3.78) vs. Female Non-Earned
Degree HS GPA (3.67)• Female Earned Degree HS GPA (3.78) vs. Male Non-Earned
Degree HS GPA (3.70)• Male Earned Degree HS GPA (3.77) vs. Male Non-Earned
Degree HS GPA (3.70)• Male Earned Degree HS GPA (3.77) vs. Female Non-Earned
Degree HS GPA (3.67)
21
Student Characteristics: High School GPA by Primary Ethnicity• For each Primary Ethnicity group, the HSGPA of the earned degree
group was higher than the non-degree earning group (F=68.95, df=7, p<.000)
• Sixteen TukeyHSD contrasts were statistically significant
3.74 3.73 3.86 3.773.70 3.65 3.77 3.71
0
1
2
3
4
AA AI AP HA
Earned Degree No Degree
22
Student Characteristics: High School GPA by Gender and Primary Ethnicity• For each Primary Ethnicity and Gender group, the HSGPA of the
earned degree group was higher than the non-degree earning group (F=68.95, df=7, p<.000)
• 54 (of 120) TukeyHSD contrasts were statistically significant3.72 3.75 3.74 3.73 3.86 3.86 3.79 3.773.71 3.65 3.67 3.65 3.84 3.70 3.68 3.73
0
1
2
3
4
AA-Male AA-Female AI-Male AI-Female AP-Male AP-Female HA-Male HA-Female
Earned Degree No Degree
23
Student Characteristics: Nomination Scores
• Scholars that earn a degree have higher nomination composite scores than Scholars that do not earn a degree
• Degree earners have a 77.49 mean composite score compared to 76.10 for non-degree earners (t= 5.3582, df=799.943, p<.000)
76.10
77.49
0 25 50 75 100
No Degree
Earned Degree
24
Student Characteristics: Nomination Scores by Gender• Female and male Scholars that earn a degree have higher
nomination composite scores than female and male Scholars that do not earn a degree, respectively (F=15.61, df=3, p<.000)
• Significant TukeyHSD contrasts:• Female Earned Degree score (77.49) vs. Female Non-Earned
Degree HS GPA (76.26)• Female Earned Degree HS GPA (77.49) vs. Male Non-Earned
Degree HS GPA (75.86)• Male Earned Degree HS GPA (77.50) vs. Male Non-Earned
Degree HS GPA (75.86)• Male Earned Degree HS GPA (77.50) vs. Female Non-Earned
Degree HS GPA (76.26)
25
Student Characteristics: Nomination Scores by Primary Ethnicity• AP and HA Scholar degree earners have nomination scores higher
than non-degree earners. AA and AI degree earner nomination scores are slightly lower than non-degree earners (F=86.6, df=7, p<.000)
• Fifteen TukeyHSD contrasts were statistically significant
78.4 73.7 78.5 77.378.4 73.8 78.1 76.9
0
25
50
75
100
AA AI AP HA
Earned Degree No Degree
26
Student Characteristics: Nomination Scores by Gender and Primary Ethnicity• The following Gender/PE degree earner groups have nomination
scores higher than non-degree earners: AA males, AI males, AP females, HA males, HA females. (F=41.40, df=15, p<.000)
• 53 (of 120) TukeyHSD contrasts were statistically significant
78.5 78.373.1 74.0
78.3 78.5 77.5 77.278.3 78.472.7 74.4
78.5 77.9 76.9 76.9
0
25
50
75
100
AA Males AA Females AI Males AI Females AP Males AP Females HA Males HA Females
Earned Degree No Degree
27
Student Characteristics: Nomination Score AreasCognitive
• Curriculum rigor • Overall academic achievement • Structure of/use of language in essays
Non-Cognitive
• Positive self-concept/self-esteem • Realistic self-appraisal • Understanding and navigation of social and organizational
systems • Preference for long-term over immediate need • Successful leadership experience • Community service • Non-traditional, Self-directed acquisition of knowledge or skill • Evidence of strong support person
28
Student Characteristics: Nomination Score Correlation ResultsSignificant Cognitive Correlations
• Curriculum rigor (r=0.1445, p <.000)• Overall academic achievement (r=0.1369, p<.000)• Structure of/use of language in essays (r=0.769, p<.000)• Cognitive composite (r=.1634,p<.000)
Significant Non-Cognitive Correlations
• Positive self-concept/self-esteem (r=0.0349, p=.007)• Understanding and navigation of social and organizational
systems (r=0.0312, p=0.16)• Preference for long-term over immediate need (r=0.0441,
p=.001)• Non-Cognitive composite (0.0260, p=.045)
29
Student Characteristics: Nomination Score Differences by Area
0.37 0.36
0.080.05
0.10 0.11
0.03-0.02 -0.01 0.01
0.22
0.12
-0.1
0.0
0.1
0.2
0.3
0.4
0.5C
urri
culu
m R
igor
Aca
dem
ic A
chie
vem
ent
Sel
f-C
onc
ept
Rea
listic
Sel
f-A
ppra
isal
Nav
igat
ing
So
cial
Sys
tem
s
Lon
g-T
erm
Goa
ls
Lead
ersh
ip
Co
mm
unity
Ser
vice
Kn
ow
ledg
e A
cqui
red
Sup
po
rt P
erso
n
Ess
ays
Ave
rag
e D
iffer
ence
30
Student Characteristics: Nomination Score t-test ResultsSignificant Cognitive Mean Differences
• Curriculum rigor (d= 0.37, t=9.439, p <.000)• Overall academic achievement (d= 0.36, t=9.438, p <.000)• Structure of/use of language in essays (d= 0.22, t=5.152, p
<.000)• Cognitive composite (d= 0.94, t=10.47, p <.000)
Significant Non-Cognitive Mean Differences
• Positive self-concept/self-esteem (d= 0.08, t=2.227, p =.026)• Understanding and navigation of social and organizational
systems (d=0.10, t=2.114, p =.035)• Preference for long-term over immediate need (d=0.11,
t=2.950, p =.003)• Non-Cognitive composite (d=0.35, t=1.555, p =.120)
31
Student Characteristics: Nomination Scores
Area Significant For All Scholars
Significant for Degree Attainment in Five Years
Curriculum Rigor Yes Yes
Academic Achievement Yes Yes
Essays Yes Yes
Cognitive Index Yes Yes
Yes means the correlation between the area and degree attainment was statistically significant at the .05 level
Cognitive Areas
32
Area Significant For All Scholars
Significant for Degree Attainment in Five Years
Self-Concept Yes Yes
Realistic Self-Appraisal Yes
Navigating Social Systems Yes Yes
Long-Term Goals Yes Yes
Leadership Yes
Community Service Yes
Knowledge Acquired Yes
Support Person Yes
Non-Cognitive Index Yes
Yes means the correlation between the area and degree attainment was statistically significant at the .05 level
Non-Cognitive Areas
Student Characteristics: Nomination Scores
33
Student Characteristics: STEM Major
• Scholars that are STEM majors graduate at higher rates than non-STEM majors
• STEM majors have 92.9% graduation rate compared to 89.9% for non-STEM majors (X2= 11.3737, df=1, p<.000)
90.7%
89.9%
92.9%
0% 25% 50% 75% 100%
Overall
Non-STEM
STEM
Graduation Rate
34
Student Characteristics: STEM Major by Gender
• STEM and Non-STEM females have higher graduation rates than STEM and NON-STEM males (X2= 260.1778, df=3, p<.000)
94.5% 90.7%90.3% 88.6%
0%
25%
50%
75%
100%
Female Male
STEM Non-STEM
35
Student Characteristics: STEM Major by Primary Ethnicity• Graduation rates for all PE groups are higher for STEM majors than
non-STEM majors except for HA Scholars (X2= 219.9267, df=7, p<.000)
93.9%
78.5%
97.0% 92.5%93.3%
70.7%
94.7% 92.7%
0%
25%
50%
75%
100%
AA AI AP HA
STEM Non-STEM
36
Student Characteristics: Deferment Types
• Deferment Types
• Academic
• Personal Hardship
• Medical
• Service
• Emergency
• Personal (Administrative): Includes only Scholars that were given this deferment prior to Senior year
• Scholars Considered
• Year Confirm: 2000-2007
• Freshman Start Point
37
Student Characteristics: Graduation Rates by Deferment Type
Type Graduates Population Graduation Rate
Academic 451 519 86.9%
Emergency 21 23 91.3%
Medical 114 136 83.8%
Personal (Administrative)^ 91 230 39.6%
Personal Hardship 456 615 74.1%
Service 24 28 85.7%
Two or More Types 96 210 45.7%
No Deferments 6321 6631 95.3%
^May be low due to lack of information on graduation status
38
Student Characteristics: Graduation Rates by Deferment Type and PE Group
Type AA AI AP HA Overall
Academic 86.5% 74.2% 93.3% 91.0% 86.9%
Emergency 94.4%* -- 50.0%* 100%* 91.3%*
Medical 82.0% 71.8% 100%* 93.3% 83.8%
Personal (Administrative)^
43.6% 22.8% 31.3%* 62.2% 39.6%
Personal Hardship 77.8% 46.3% 86.0% 81.0% 74.1%
Service 60.0%* 71.4%* 100%* 100%* 85.7%*
Two or More Types 56.9% 21.7% 61.1%* 56.9% 45.7%
No Deferments 96.4% 86.9% 97.6% 95.4% 95.3%
*Less than 30 Scholars
^May be low due to lack of information on graduation status
39
Student Characteristics: Graduation Rates by Deferment Time
Type Graduates Population Graduation Rate
0.5 AY 369 428 86.2%1 AY 738 1085 68.0%1.5 AY 74 126 58.7%2 AY 50 85 58.8%>2 AY 22 37 59.5%No Deferments 6321 6631 95.3%
86.2%
68.0%
58.7% 58.8% 59.5%
95.3%
0.5 AY 1 AY 1.5 AY 2 AY >2 AY No Deferments
Graduation Rate by Academic Year Deferment Time
40
Factor Being Developed:Student Engagement
41
Engagement Index
• Annual GMS Engagement Survey
• Five Engagement Areas• Academic Engagement (Degree goal, Study habits, Class
Preparation) • Campus Engagement (Activity participation, Campus service
usage)• Community Engagement (Volunteer/Public Service)• GMS Program Engagement (Knowledge/use of program
resources, Program activity participation, Scholar engagement)• Non-Engagement (Non-academic related employment/time)
• Individual index areas are combined for an overall index
42
Engagement Index
• Engagement level is defined as high, moderate, low, or no engagement in each area.
• Overall Engagement Formula:• Academic + Campus + Community + Program – Non-
engagement
43
Engagement Index: Preliminary Results All Institutions
Engagement Area High Moderate Low No
Academic 42.9% 55.1% 2.0% 0.0%
Campus 77.6% 17.3% 4.9% 0.2%
Community 26.9% 37.7% 29.4% 6.0%
Program 11.8% 41.8% 44.4% 2.1%
Non-Engagement Area High Moderate Low No
Non-engagement level 8.6% 34.8% 7.2% 49.5%
Overall Engagement High Moderate Low No
Combined 15.7% 65.0% 19.2% 0.1%
44
Engagement Index: Preliminary Results Campus Engagement Manager Institutions
Engagement Area High Moderate Low No
Academic 40.8% 57.4% 1.8% 0.0%
Campus 75.8% 18.1% 5.8% 0.3%
Community 25.1% 38.8% 36.1% 0.0%
Program 19.0% 47.3% 32.1% 1.6%
Non-Engagement Area High Moderate Low No
Non-engagement level 8.1% 34.5% 6.0% 51.5%
Overall Engagement High Moderate Low No
Combined 17.8% 65.0% 17.1% 0.1%
45
Engagement Index: Comparison of High Engagement Levels
Academic Campus Community Program Non-Engagement Combined
40.8%
75.8%
25.1%19.0%
8.1%
17.8%
44.6%
79.0%
28.3%
6.0%9.0%
14.1%
High Engagement Levels
CEM Institutions Non-CEM Institutions
46
Engagement Index: Questions for Next Steps
• Engagement Scores by Level: Do we adjust the cut-scores for each level?
• Weighting: Do we weight engagement levels differently when developing the overall engagement score?
• Outcomes: What outcomes are appropriate to link to engagement?
47
In Development: Applying this Knowledge
48
Applying this Knowledge
• Goal is to use this information to develop a dashboard in the following areas
• Graduation: Due to high graduation rates, valid prediction model can not be developed. Instead will look at success/risk level in each area
• Graduate school in program funded area: Completing a logistic regression model for this outcome
49
Applying this Knowledge: Graduation
• Graduation: To inform on graduation likelihood, index will be created for each Scholar
Scholar Name
Nomination Score
GPA First-Gen
Institution Type
Deferment
Engagement
Overall
Scholar One Sample H H H H H H H
Scholar Two Sample L L L L L L L
• Decisions to be made: Areas to include, risk level for each area, how risk areas will be combined.
50
Applying this Knowledge: Graduate School
• Program funds students for graduate school in these areas:• Computer Science• Education• Engineering• Library Science• Mathematics• Public Health• Science
• Independent Variables being evaluated: Gender, PE, Major, GPA, Institution, First-generation status, Engagement.
• Decisions: Other variables to be considered
51
Discussion
Top Related