SAIR 2011 – Atlanta, Georgia
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Transcript of SAIR 2011 – Atlanta, Georgia
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Strategies for Building Graduate Student Completion and Time to Degree Measures
Concurrent Panel Session
SAIR 2011 – Atlanta, Georgia
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Presenters
Kristi D. FisheroUniversity of Texas at Austin
Julius L. GanttoUniversity of Georgia
Susan E. Moreno oUniversity of Houston
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Goals for PresentationPresentations from 3 different
Universities on Graduate Student Completion and Time to Degree (TTD) Models
o Type of cohort models and Time to Degree measurements selected
o Challenges Faced & Solutions
o Strengths and Limitations of Models
Q&A
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Types of TTD MeasurementsTotal Time to Degreeo Number of years between the awarding of the
baccalaureate degree and the attainment of the advanced degree
o National Research Council’s Survey of Earned Doctorates
Elapsed Time to Degreeo Counts the time from entry into a graduate
program to the awarding of the degreeo Many Institutions use this Measurement
Registered Time to Degreeo Only the time in which the student was actually
registered in graduate school
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Cohort Types for ModelsForward Model or New Enrollment
cohorts group students by the year in which the students entered a graduate program
Backward Model or Degree Cohorts groups students by the year in which the graduate degree was conferred
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U. T. Austin – Time to Degree & Graduate Rates and Retention Models
Presented By: Kristi D. FisherAssociate Vice ProvostOffice of Information Management and AnalysisThe University of Texas at Austin
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The University of Texas at Austin
• Nearly 13,000 Graduate Students• 5,200 Doctoral• 6,000 Master’s• 1,200 Law• 500 Pharm. D.
• 240 Graduate Programs• 86 Doctoral• 154 Master’s
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U.T. Austin Models
Two ways we are using graduate program TTD right now:1. Graduate Student Information portal
project (GSI)• Uses “major forward” model
2. Texas Higher Education Coordinating Board’s (THECB) “18 Characteristics” mandatory reporting• Uses degrees-granted (backward)
model
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U.T. Austin Portal Project Focus on GSI “portal” – though is also a B. I. (data warehouse) project….• Extremely high-profile project• Board, new Regents, pressure on graduate TTD• Beginning a program review process internally• Pursuit of efficiency AND excellence in all
programs (with pressure from budget constraints)
• Starting with primarily Doctoral programs (86) and will follow with Masters programs
• Influencing institutional policies and processes
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U.T. Austin “Major Forward”
“Major Forward” model offers insight into:• Progression for all doctoral students entering
specific major/year (not just completers)• Effectiveness of recruiting program over time• Program degree production efficiency over
time• Financial support trends and their impact• Cost of attrition (opportunity cost and actual)
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A Few Hurdles…Hazards and Considerations:• Difficult to distinguish between “primarily
doctoral” and “primarily master’s” in some cases
• Cannot rely on student’s technical classification• Major changes - some disciplines very closely
related• Master’s earned along the way included in PhD
TTD• CIP code issues – changes over time• Organizational changes• Dual degrees (defer to “owning” program)• “Simple math”
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Doctoral Time to Degree- “Major Forward” Model
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Doctoral Time to Degree – Specific Department
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Doctoral Rates and Retention– Major Forward Model
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Doctoral Rates and Retention– Specific Department
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Doctoral Financial Support for Department – Inflation-Adjusted
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Doctoral Financial Support for Department – Actual Data
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Doctoral Financial Support for Department – Exited, No Degree
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Doctoral Financial Support for Department – Exited, Master’s Only
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Doctoral Financial Support Totals – ECONOMICS Department
About 3% of 20 Years’ Financial Support Budget are Sunk Costs ( = Opportunity Cost)
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Doctoral Financial Support Totals– Some OTHER Dept.
Nearly 20% of 20 Years’ Financial Support Budget
DOWN THE DRAIN!!!!!
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Important takeaways…It’s not just about how long it takes to succeed, but also time and resources lost to unsuccessful outcomes.
Model captures EFFICIENCY, but not EXCELLENCE… WE WANT BOTH!!!
(i.e. need Placement Data!)
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Graduate Student Retention and Completion
Tracking SystemJulius Gantt
Office of Institutional Research
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OriginsStarted as an undergraduate
retention systemoUsed to track the IPEDS freshmen
cohortoUsed to track information about
transfer and other undergraduate students Completion Stop-Out Drop-Out TTD And more…
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Origins Initial start to the graduate system due to
UGA’s inclusion as a pilot university in CGS’s Ph.D. Completion Projecto IR office partnered with UGA’s Graduate School
to provide required data on 13 degree programs
oRequired large amounts of data on doctoral students including demographical, retention, and completion
oA number of problems occurred along the way, mainly definitional data in main student database did not allow for easy tracking of students
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OriginsAfter CGS’s pilot data collection
completed, decision was made to take what we learned (IR and Graduate School) and make an expanded analysis of all doctoral programs (over 90 programs)
Two outcomes came from this:oOutput displayed in an on-line drillable
formatoUnderlying data was placed into a data
repository – precut, predefined variables that were the same (definitional wise) for all students
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Growth of SystemThe system became popular and
was highlighted by Dean of Graduate School and other senior administrators
System used in UGA’s response to NRC doctoral rankings
Decision made to expand system to include students in Master’s programsoThis also includes on-line drillable
reports and underlying pre-defined data
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Data Repository - OverviewUsed by IR staff members onlyUsed to track students from time of initial
enrollment to leaving the university (drop-out or completion)
Demographic, academic, enrollment, credit hours, financial aid, student activities, and other detailed data are captured in this system
Students are placed into fiscal year cohorts, but able to be tracked by term of enrollment
Allows various style reports or files to be created
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Data Repository – Unique FeaturesStudents are placed into pre-defined
variablesoThis allows students from multiple years to be
combined into analysis (same thing is being measured by same definitions over time)
oEx: Term data is defined as Year1_Term1oTime-to-Degree (TTD) and Time-to-Withdrawal
(TTW) tracked based on 1st term of enrollment
Tracking of students across programsoStudents who switch degree programs – counted
as dropout of 1st program, new enrollee in 2nd
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Data Repository – Unique Features
Tracking of students moving “up” and “down” degree levelsoMaster’s students who decide to pursue
PhD Student completes masters – enrollment
in PhD based on 1st term of PhD enrollment
Student doesn’t complete masters – enrollment in PhD based on 1st term of masters enrollment (back date data – as long as same major for both degree programs) and is considered a master’s dropout
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Data Repository – Unique Features
Tracking of students moving “up” and “down” degree levelsoPhD students who decide to “drop
down” to masters level 1st term of enrollment in master’s is
based on 1st term in PhD program (back date data – as long as same major in both degree programs)
Is considered a PhD dropout If student enrolls later in PhD program –
considered a new enrollee
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Drillable Reports - OverviewThree reports built for both Masters
and Doctoral students (using ColdFusion)o Masters Retention by Degree Programso Doctoral Retention by Degree Programso Doctoral Retention by Degree Programs
10 Year SnapshotReports can be viewed based ono The entire Universityo Main Campus and Extended Campuses
(Masters only)o College/Schoolo Departmento Program Major
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Drillable Reports - Overview
Reports contain the following types of informationo # Students in the Cohort (Grouped by
Summer-Fall-Spring terms)o Graduation and TTD Informationo Retention and Enrollment Informationo Withdrawal and TTW Information
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DRILLABLE REPORTS - EXAMPLES
Campus-Wide
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DRILLABLE REPORTS - EXAMPLES
College/School
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DRILLABLE REPORTS - EXAMPLES
Department
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DRILLABLE REPORTS - EXAMPLES
Program Major
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Graduation Rate and Time To Degree Models Presented By:Susan MorenooDirectoroOffice of Institutional ResearchoUniversity of Houston
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Impetus for UH
New Chancellor/President in 2008
18 Characteristics
National Research University Fund (NRUF)
Houston Endowment Support
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UH Data Issues
First semester determination
Lack of attention to data entry
Lack of graduate school milestones
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Program N % N % N %Business Administration - Finance
3 1 33.3 2 2 100.0 3 2 66.7 66.7
Curriculum And Instruction
24 11 45.8 33 15 45.5 61 37 60.7 50.7
Chemical Engineering 6 3 50.0 15 11 73.3 19 16 84.2 69.2
History 4 1 25.0 3 2 66.7 14 9 64.3 52.0
Physics 5 1 20.0 7 5 71.4 34 31 91.2 60.9
Physiological Optics 3 3 100.0 2 2 100.0 7 6 85.7 95.2
Pharmaceutics 1 1 100.0 100.0
Social Work 3 1 33.3 4 2 50.0 10 5 50.0 44.4
10 Year Graduation
Start #
10 Year Graduation
Avg. of 3 Yr.
Percents
1999
Start #
1998 2000
Start #
10 Year Graduation
Graduation Rate
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Graduation Rate
Problems Encountered
oSmall cohort sizes
oNo doctoral students despite expectations
oAdmitted to a masters program
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Graduation RateDecisions
oTexas Coordinating Board’s Accountability
oAll doctoral students (or masters)
oLook back three years to how reported
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Time To Degree
N Mean N Mean N MeanBus Admn-Finance, PHD
2 5.0 4 5.7 4 6.8
Curr & Instruct, EDD 34 6.6 31 8.3 18 8.3
Chem Engr, PHD 11 5.4 11 5.8 14 4.5
History, PHD 6 6.9 9 9.9 10 8.2
Physics, PHD 9 5.6 6 6.5 13 5.9
Physiological Opt, PHD
3 6.2 4 6.3 2 7.7
Pharmaceutics, PHD 3 4.7 2 6.2
Social Work, PHD 2 8.2 4 7.8 7 6.5
ProgramFY 2008 FY 2009 FY 2010
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Time To DegreeProblems Encountered
oDetermining the starting point
oDid not match with SED
oAdministrators and Department Chairs doubted averages
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Time To DegreeDecisions
oStart of graduate school at UH
oCount every semester since first semester
oHad department disprove the findings
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ImplicationsGreater attention to data in the
system
On-going monitoring of graduate/professional student data
Beginning to establish better business processes and policies for graduate/professional programs
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Where are we going from here…Houston Endowment Grant requires
annual accountability measures for both masters and doctoral students.oRecruitment
oFunding
oSpecial support for Arts and Humanities
Restructuring of Graduate/Professional Area