Strategies for Building Graduate Student Completion and Time to Degree Measures

Concurrent Panel Session

SAIR 2011 – Atlanta, Georgia

Presenters



Kristi D. Fisher

o

University of Texas at Austin



Julius L. Gantt

o

University of Georgia



Susan E. Moreno

o

University of Houston

Goals for Presentation



Presentations 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 Measurements

 Total Time to Degree o o Number of years between the awarding of the baccalaureate degree and the attainment of the advanced degree National Research Council’s Survey of Earned Doctorates  Elapsed Time to Degree o o Counts the time from entry into a graduate program to the awarding of the degree Many Institutions use this Measurement  Registered Time to Degree o Only the time in which the student was actually registered in graduate school

Cohort Types for Models

 Forward 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. Fisher

Associate Vice Provost Office of Information Management and Analysis The 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 System

Julius Gantt Office of Institutional Research

Origins

 Started as an undergraduate retention system o Used to track the IPEDS freshmen cohort o Used 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 Project o IR office partnered with UGA’s Graduate School to provide required data on 13 degree programs o Required large amounts of data on doctoral students including demographical, retention, and completion o A number of problems occurred along the way, mainly definitional  data in main student database did not allow for easy tracking of students

Origins

  After 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: o Output displayed in an on-line drillable format o Underlying data was placed into a data repository – precut, predefined variables that were the same (definitional wise) for all students

Growth of System

 The 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 programs o This also includes on-line drillable reports and underlying pre-defined data

Data Repository - Overview

 Used by IR staff members only  Used 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 Features

 Students are placed into pre-defined variables o This allows students from multiple years to be combined into analysis (same thing is being measured by same definitions over time) o Ex: Term data is defined as Year1_Term1 o Time-to-Degree (TTD) and Time-to-Withdrawal (TTW) tracked based on 1 st term of enrollment  Tracking of students across programs o Students who switch degree programs – counted as dropout of 1 st program, new enrollee in 2 nd

Data Repository – Unique Features

 Tracking of students moving “up” and “down” degree levels o Master’s students who decide to pursue PhD  Student completes masters – enrollment in PhD based on 1 st term of PhD enrollment  Student doesn’t complete masters – enrollment in PhD based on 1 st 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 levels o PhD students who decide to “drop down” to masters level    1 st term of enrollment in master’s is based on 1 term in PhD program (back date data – as long as same major in both degree programs) st Is considered a PhD dropout If student enrolls later in PhD program – considered a new enrollee

Drillable Reports - Overview

 Three reports built for both Masters and Doctoral students (using ColdFusion) o Masters Retention by Degree Programs o Doctoral Retention by Degree Programs  o Doctoral Retention by Degree Programs  10 Year Snapshot Reports can be viewed based on o The entire University o o Main Campus and Extended Campuses (Masters only) College/School o o Department Program Major

Drillable Reports - Overview

 Reports contain the following types of information o # Students in the Cohort (Grouped by Summer Fall-Spring terms) o Graduation and TTD Information o Retention and Enrollment Information o 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 Moreno o Director o Office of Institutional Research o University 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

Graduation Rate

Program Business Administration - Finance Curriculum And Instruction Chemical Engineering History Physics Start # 3 24 6 4 5 Physiological Optics Pharmaceutics Social Work 3 3 1998 10 Year Graduation N % 1 11 3 1 1 3 1 33.3

45.8

50.0

25.0

20.0

100.0

33.3

Start # 1999 10 Year Graduation N % 2 33 15 3 7 2 4 2 15 11 2 5 2 2 100.0

45.5

73.3

66.7

71.4

100.0

50.0

Start # 2000 10 Year Graduation N % 3 61 19 14 34 7 1 10 2 37 16 9 31 6 1 5 66.7

60.7

84.2

64.3

91.2

85.7

100.0

50.0

Avg. of 3 Yr. Percents 66.7

50.7

69.2

52.0

60.9

95.2

100.0

44.4

Graduation Rate



Problems Encountered

o Small cohort sizes o No doctoral students despite expectations o Admitted to a masters program

Graduation Rate



Decisions

o Texas Coordinating Board’s Accountability o All doctoral students (or masters) o Look back three years to how reported

Time To Degree

Program Bus Admn-Finance, Chem Engr, PHD History, PHD Physics, PHD Physiological Opt, Social Work, PHD N FY 2008 2 34 11 6 9 3 Mean 5.0

6.6

5.4

6.9

5.6

6.2

2 8.2

4 31 11 3 4 9 6 4 N FY 2009 Mean 5.7

8.3

5.8

9.9

6.5

6.3

4.7

7.8

4 18 14 10 13 2 2 7 N FY 2010 Mean 6.8

8.3

4.5

8.2

5.9

7.7

6.2

6.5

Time To Degree



Problems Encountered

o Determining the starting point o Did not match with SED o Administrators and Department Chairs doubted averages

Time To Degree



Decisions

o Start of graduate school at UH o Count every semester since first semester o Had department disprove the findings

Implications

 Greater 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.

o Recruitment o Funding o Special support for Arts and Humanities  Restructuring of Graduate/Professional Area

Contact Info

 Kristi D. Fisher [email protected]

 Julius L. Gantt [email protected]

 Susan E. Moreno [email protected]