48X36 Poster Template - Washington State University

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Transcript 48X36 Poster Template - Washington State University

Academic Performance and Persistence of Undergraduate Students at a Land-Grant Institution:
A Statistical Analysis Utilizing Detailed Institutional Data
Fran Hermanson, Vicki McCracken, and Diem Nguyen
Washington State University
INTRODUCTION
GRADUATION PROFILE
Graduation Profile by Life Table Survival Estimates
 Improving student success in postsecondary
education is a key federal, state, and university
objective that is inseparable from the focus on
increasing student access.
 In Washington State, about 59 percent of college
students graduate within six years. At Washington
State University (WSU), a six-year graduation rate
is approximately 68 percent.
 These statistics raise concerns about the
retention and graduation of college students and the
need for improving student success at WSU.
 This study uses WSU institutional data to
analyze factors associated with academic
performance and persistence of WSU students and
provide some policy implications for improving the
retention and graduation rates.
KEY FINDINGS
Duration
Number
Cum.
Con. Prob. of
Non-
(term)
Graduated
Graduated
Graduation
Graduation
0
2
3
4
5
6
7
8
9
10
11
12
0
1
3
26
19
109
152
1927
721
688
141
160
0
1
4
30
49
158
310
2237
2958
3646
3787
3947
0.0000
0.0002
0.0005
0.0045
0.0033
0.0188
0.0267
0.3484
0.2001
0.2386
0.0642
0.0779
1
0.9998
0.9993
0.9949
0.9916
0.9729
0.9469
0.6170
0.4936
0.3758
0.3517
0.3243
Graduation
R. Lifetime
Hazard
0.0000
0.0002
0.0007
0.0051
0.0084
0.0271
0.0531
0.3830
0.5064
0.6242
0.6483
0.6757
9.9480
7.9480
6.9487
5.9508
4.9688
3.9820
3.0603
2.1708
.
.
.
.
0.0000
0.0002
0.0005
0.0045
0.0033
0.0190
0.0271
0.4219
0.2223
0.2710
0.0664
0.0811
STATISTICAL MODELS
1. Performance Model
 High School GPA is a significant predictor of first semester
college GPA and positively affects the probability of graduation
(both five and six year).
 SAT/ACT is a solid (positive) predictor of first semester
WSU GPA but does not significantly impact the probability of
graduation.
 Varsity Athlete status increases the odds of student
graduation, and is linked to higher GPAs.
 Federal Pell Grant eligibility is associated with lower WSU
GPAs and probabilities of completing the degree, indicating
financial constraints negatively impact student success.
 Students who take Biology/Chemistry/Math all in the first
semester have significantly lower first semester GPAs but
graduate at similar rates as their counterparts.
 Despite differences in graduation rates by race/ethnic groups,
the race/ethnicity variables are not significant in the multiple
regression/logistical analyses.
Yi is the WSU GPA of student i for the first semester.
Xi is a vector of explanatory variables including: race/ethnicity,
gender, age, residency, HSGPA, SAT/ACT, Pell eligibility, full/parttime status, whether a varsity athlete, affiliation with Greek system or
Honors College, simultaneously taking Biology/Chemistry/Math, and
if in a STEM (Science, Technology, Engineering, and Math)
discipline.
 Non-continuous enrollment
probability of graduation.
significantly
lowers
the
 Washington residents had lower first semester GPAs, but had
higher probabilities of graduating.
2. Graduation Model
SELECTED RESULTS
Zi is a binary random variable, whose value equals 1 if student i
graduated by the 6th (or 5th) year and 0 if not; and Pi is the
graduation probability for student i.
Xi is a vector of explanatory variables with additional predictors: first
semester GPA (adjusted), transferred credits, and stop-out.
METHODOLOGY
 This study applies statistical techniques to
determine factors affecting student performance
and graduation at WSU.
DATA
 OLS regression is used for the first-semester
performance model with GPA as the response
variable and logistic regression is used for the
graduation model with a binary response .
 Analysis based on institutional data for 2
cohorts of students that entered WSU (Pullman
campus) as new freshmen in fall 2002 and fall
2003.
 The survival analysis method is used to take
into account the longitudinal nature of the
student progression and the censoring data
problem.
 Detail included information about the student
prior to enrolling and then at the end of 1st
semester, 2nd semester, and subsequent semesters
until 12th semester.
 Pre-college and post-enrollment variables,
student
demographics,
and
institutional
characteristics are examined in both performance
and graduation models.
 Analyzed dataset consisted of 5841 students, of
which 1894 are censored (had not graduated by
the 12th semester), accounting for over 32 percent
of the 2 cohorts.
Variables
First-term Performance
Intercept
GENDER
AGE
HSGPA
STEM
SAT
FULLTIME
GPASEM1
HONOR
RESIDENCY
GREEK
ATHLETE
BCMATH
PELL
AVLOAN
WHITE
BLACK
HISPANIC
ASIAN
OTHER
TRANSCREDIT
STOPOUT
COHORT
*** p ≤ 0.01 ** p ≤ 0.05
-1.7390
0.1089***
0.0380**
0.7949***
0.1589***
0.0919***
0.2334**
0.1765***
-0.0910***
0.0722***
0.1171***
-0.3553***
-0.0064
-0.0036
0.0204
-0.0020
-0.0301
-0.0763
0.0159
0.0376**
Five-year Graduation
Six-year Graduation
-3.5049
0.2612***
-0.0805
0.8617***
1.1954***
-0.0205
1.9872***
1.1657***
-0.0323
0.5831***
1.0210***
0.8128***
-0.3699
-0.2173***
0.0198
0.2362
0.1392
-0.2104
0.1911
0.2798
0.0162***
-2.5709***
0.0928
-3.6476
0.0673
-0.1015
1.0598***
1.6277***
-0.0477
1.9384***
1.2546***
0.1649
0.7308***
1.0987***
0.8012***
0.1523
0.0090
0.0575***
0.4342
0.4442
-0.0850
0.3875
0.4694
0.0182***
-2.2866***
0.0729
IMPLICATIONS
 The empirical results suggest an admission process
selecting students based on individual potential for
success should consider factors in addition to high
school GPA and SAT/ACT.
 Retention efforts should identify students based on
other risk factors (in addition to high school GPA and
SAT), such as financial aid, residency, housing,
enrollment status, running-start, etc.
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