Strategies for Building Graduate Student Completion and Time to Degree Measures

Concurrent Panel Session

SAIR 2011 – Atlanta, Georgia

Presenters

Kristi D. FisheroUniversity of Texas at Austin

Julius L. GanttoUniversity of Georgia

Susan E. Moreno oUniversity of Houston

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

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

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

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

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

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

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

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)

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”

Doctoral Time to Degree- “Major Forward” Model

Doctoral Time to Degree – Specific Department

Doctoral Rates and Retention– Major Forward Model

Doctoral Rates and Retention– Specific Department

Doctoral Financial Support for Department – Inflation-Adjusted

Doctoral Financial Support for Department – Actual Data

Doctoral Financial Support for Department – Exited, No Degree

Doctoral Financial Support for Department – Exited, Master’s Only

Doctoral Financial Support Totals – ECONOMICS Department

About 3% of 20 Years’ Financial Support Budget are Sunk Costs ( = Opportunity Cost)

Doctoral Financial Support Totals– Some OTHER Dept.

Nearly 20% of 20 Years’ Financial Support Budget

DOWN THE DRAIN!!!!!

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!)

Graduate Student Retention and Completion

Tracking SystemJulius Gantt

Office of Institutional Research

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…

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

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

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

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

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

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

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

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

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

DRILLABLE REPORTS - EXAMPLES

Campus-Wide

DRILLABLE REPORTS - EXAMPLES

College/School

DRILLABLE REPORTS - EXAMPLES

Department

DRILLABLE REPORTS - EXAMPLES

Program Major

Graduation Rate and Time To Degree Models Presented By:Susan MorenooDirectoroOffice of Institutional ResearchoUniversity of Houston

Impetus for UH

New Chancellor/President in 2008

18 Characteristics

National Research University Fund (NRUF)

Houston Endowment Support

UH Data Issues

First semester determination

Lack of attention to data entry

Lack of graduate school milestones

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

Graduation Rate

Problems Encountered

oSmall cohort sizes

oNo doctoral students despite expectations

oAdmitted to a masters program

Graduation RateDecisions

oTexas Coordinating Board’s Accountability

oAll doctoral students (or masters)

oLook back three years to how reported

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

Time To DegreeProblems Encountered

oDetermining the starting point

oDid not match with SED

oAdministrators and Department Chairs doubted averages

Time To DegreeDecisions

oStart of graduate school at UH

oCount every semester since first semester

oHad department disprove the findings

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

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

Contact InfoKristi D. Fisher

kfisher@austin.utexas.edu

Julius L. Gantt jgantt@uga.edu

Susan E. Moreno semoreno@uh.edu