Success and Attrition Factors for High Achieving Underrepresented/ Underserved Students Barry Nagle, GMS/UNCF Senior Research Associate Jin Liu, Research Analyst National Scholarship Providers Association Annual Conference Pittsburgh, PA October 2014
Success and Attrition Factors for High Achieving Underrepresented / Underserved Students Barry Nagle , GMS/UNCF Senior Research Associate Jin Liu, Research Analyst National Scholarship Providers Association Annual Conference Pittsburgh, PA October 2014. Background: GMS Program. - PowerPoint PPT Presentation
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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
• 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%
• 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
• 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 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