Post on 22-Feb-2016
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School of BusinessSchool of Business
Are Students Dropping Out or Dragging Out the College
Experience? &Modeling the Enrollment Path
Leslie S. Stratton & James N. Wetzel
Virginia Commonwealth UniversityResearch funded in large part by an AIR Research Grant
2012 Presentation at NEAIR Conference
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Plan•Motivation•Briefly review some literature •Data•Goals of each paper•Results of Paper #1•Results of Paper #2•Conclusion
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Motivation•Completion rates are a concern.
▫ Enrollment is up, but graduation rate is unchanged (63%). 45% for African Americans, 54% for Hispanics, 54% for low
income, and 53% for first generation college students. •Benefits accrue primarily upon graduation. •Costs are incurred upon enrollment.
▫Shared by students/families and public.•Dept of Education is targeting schools with
low graduation rates.
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Literature•Studies of college outcomes are
proliferating. •Many control for socioeconomic status:
▫ Paulsen, St. John (2002), Swail, Cabrera, Lee (2004), Ishitani (2003, 2006), Titus (2006), … review by Kuh et al. (2006)
& find these populations are disadvantaged.
•Controlling for academic background is even more important ▫ Adelman 2004, Carneiro & Heckman 2002 find
background trumps race/ethnicity.
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Literature•But, many studies are
▫based on data from 1 university,▫do not adequately control for academic
background, or▫designate success as graduation within a
particular time horizon.•Not all those who have not graduated in X
years have given up. •Many students enroll PT, stop out,
transfer.
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Contributions of 1st Paper• Multi-institution study.• Controls for SES & academic
background/ability.• Distinguishes between those not enrolled and
those still enrolled at 6 year mark.
2nd Paper • Also controls for enrollment path.
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Data•1996/2001 US Beginning Postsecondary
Survey•National sample of those beginning in
1995-96 academic year. •Restrict sample to those:
▫Who are followed through 2001▫Who initially attend 4 year institutions▫Who are age 23- & from US
•Sample of about 5820 students.
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Research Questions: Paper #1•Most studies compare graduates with
non-graduates, BUT•1) How common is persistence at the 6
year mark? •2) How does distinguishing between
those still enrolled and those not enrolled alter results of college outcome models?
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Covariates I•Demographics:
▫Gender▫Race/Ethnicity▫Age ▫Marital status ▫Parental status▫Parents’ education▫Household income
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Covariates II•Academic background/ability:
▫Standardized test scores▫High school GPA▫High school program of study
•Unemployment rate.
All observed at time of matriculation.
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Question 1: How common is persistence at the 6 year mark?
•63.2% have graduated.•23.4% are not enrolled.•13.4% are still enrolled.
•36% of those who have not graduated are still enrolled in last term observed!
•Persistence is common!
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Question 2: How does controlling for persistence alter
outcome models?•Standard analyses use logit specification
to distinguish between graduates and non-graduates.
•We use a MNL model to distinguish among 3 outcomes: graduation, persistence, drop out.
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Distinguishing between Persistence and Non-Enrollment is
Important• Statistically persistence is a distinct state. • Results by SES:
▫Disadvantaged students are less likely to graduate.
▫Hispanics are persisting. ▫1st Generation college students are dropping
out.▫African Americans and Women are split. ▫Lower income students have mixed results.
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Distinguishing between Persistence and Non-Enrollment is
Important• Biggest Factors = Academic Background
▫Those with less than stellar high school GPAs are substantially less likely to have graduated. Between 15 and 25% of these non-graduates are
still enrolled. ▫Math background and SAT scores have a
smaller marginal effect on graduation, but a similar association with persistence.
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Evidence re-Graduation• Analysis of similar sample from
Baccalaureate and Beyond survey suggests half of those still enrolled may graduate within a few years.
• Analyses of college outcomes should look at persistence!
• Is ‘dragging out’ worthwhile?
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Why the Differences? •Enrollment paths are different.
▫Hispanics are more likely to enroll part-time.
▫Income/household constraints may favor part-time or stop out behavior.
▫Less prepared students may take more remedial classes, fewer courses/term.
•Can only address this by modeling path as well as outcome 2nd Paper.
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What Path Looks Like•Initial Enrollment
▫~ 4% Part-time, 96% Full-time.•1 Year Mark
▫~ 11% Not Enrolled, 4% Part-time, 85% Full-time.
•3 Year Mark▫~19% NT, 7% PT, 71% FT, and 2%
Graduated. •5 Year Mark
▫~ 22% NT, 5% PT, 13% FT, and 60% Graduated.
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What Path Looks Like
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.50%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Enrollment Status over TimeWeighted
Grad
FT
PT
NT
Years following Matriculation
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A Discrete Time Hazard of Enrollment
• Takes initial FT/PT enrollment decision as given. • Models transitions from:
▫FT to FT, PT, NT, & graduation▫PT to FT, PT, NT, & graduation▫NT to FT, PT, & NT.
• Graduation is treated as an absorbing state.
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Specification• Uses a MNL specification to model these
movements.
• Models transitions from state j to state k as a function of ▫X = individual specific & matriculation
characteristics, ▫Wt = time varying covariates,▫Zt = past behavior, & ▫Θ captures unobserved heterogeneity.
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Specification▫X includes ~ all covariates from paper 1 + info
on first term attended (PT/FT, Spring/Fall, Semester/Quarter, …),
▫Wt includes unemployment level and change, college grades, family chars,
▫Zt includes quadratic in time spent enrolled PT, FT, NT in past, &
▫Θ is iid normal.
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Results: Predicted Path•Fixes Wt – College grades generally rise.
•Initial Enrollment: Fixed.•1 Year Mark
▫~ 12% Not Enrolled, 5% Part-time, 83% Full-time.
•3 Year Mark▫~20% NT, 7% PT, 72% FT, and 2% Graduated.
•5 Year Mark
▫~ 27% NT, 6% PT, 17% FT, and 50% Graduated.
More NT & FT, Less Graduated
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Results: Predicted Path
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 350%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Predicted Enrollment StatusUR Changes
Grad
FT
PT
NT
Time
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Results: Socio-economic indicators• Hispanics spend more time PT and NT than non-
Hispanics.• 1st Gen spend more time PT and NT than non-1st
Gen. • Blacks spend more time FT, but less time NT
than whites.• Those from lower income HHs, spend more time
NT.
• Even controlling for path, all have a lower probability of graduating.
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Results: Educational Background• Still much more important, especially high
school grades.• Low performers spend less time FT, more NT and
PT.
• Controlling for path, effect on probability of graduation is modest.
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Results: Unemployment Rate•Both level of unemployment and recent
changes are significant. •Consistent with an opportunity cost
argument:• A lower level of unemployment increases NT,
while decreasing PT & FT. Little change in graduation rate.
• Decreases in the unemployment rate appear to reduce PT enrollment and speed graduation.
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General Conclusions • Persistence 6 years after matriculation is
substantial and should be recognized and studied. - Is dragging out the college experience wise?
• Enrollment paths constitute a complex problem. ▫Disadvantaged groups appear to have lower
graduation rates, even controlling for path. ▫Academic background may play a greater role
in driving the path rather than the outcome. ▫Economic conditions will change paths and
outcomes.
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Questions?