[RESAMPLED RANGE OF WITTY TITLES]Understanding and Using the NRC Assessment of Doctorate Programs

Lydia Snover, Greg Harris & Scott BargeOffice of the Provost, Institutional Research

Massachusetts Institute of Technology • 2 Feb 2010

Overview1. Background & Context

2. Approaches to Ranking

3. The NRC Model: A Modified Hybrid

4. Presenting & Using the Results

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2*NB: All figures/data in this presentation are used for illustrative purposes only and do not represent a known institution.

Background & Context

A. History of NRC Rankings

B. MIT Data Collection Process

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Participating MIT ProgramsAeronautics and Astronautics Computer Science

Applied Biosciences Economics

Applied Mathematics Electrical and Computer Engineering

Astrophysics and Astronomy and Planetary Science

Geology and Geochemistry and Geophysics

Atmospheres, Oceans & Climate including MIT/WHOI Oceanography

History, Theory and Criticism

Biological Engineering, Health Science and Technology

Linguistics

Biology/Biochemistry and Biophysics Material Sciences and Engineering

Biology/Cell and Developmental Mathematics

Biology/Genetics and Genomics Mechanical Engineering

Chemical Engineering Neuroscience

Chemistry Operations Research

Civil and Environmental Engineering Philosophy

Cognitive Science Physics

Computer Engineering Political Science 4

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Section 2

2. Approaches to Ranking

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How do we measure program quality?• Use INDICATORS (“countable” information)

to compute a rating– Number of publications

– Funded research per faculty member

– Etc.,

• Try to quantify more subjective measures through an overall PERCEPTION-BASED RATING– Reputation

– “Creative blending of interdisciplinary perspectives”

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Section 3

3. The NRC Approach

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So how does NRC blend the two?The NRC used a modified hybrid of the two basic approaches:•In total, a 4-step process, indicator based, by field

•Process results in 2 sets of indicator weights developed through faculty surveys:

– “Bottom up” –importance of indicators

– “Top-down” – perception-based ratings of a sample of programs

•Multiple iterations (re-sampling) to model “the variability in ratings by peer raters.” *

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8*For more information on the rationale for re-sampling, see pp. 14-15 of the NRC Methodology Report

So how does NRC blend the two?STEP 1: Gather raw data from institutions, faculty & external sources on programs. Random University (RU) submitted data for its participating doctoral programs.

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RU PhysicsIndicator Value

# publications/fac 1.07

# citations/article 1.17

Median GRE 746

Gender diversity 44%

Time to degree 5.67

…

RU ChemEIndicator Value

# publications/fac 1.07

# citations/article 1.17

Median GRE 746

Gender diversity 44%

Time to degree 5.67

…

RU EconomicsIndicator Value

# publications/fac 1.07

# citations/article 1.17

Median GRE 746

Gender diversity 44%

Time to degree 5.67

…

NRCNRC

So how does NRC blend the two?STEP 2: Use faculty input to develop weights:– Method 1: Direct prioritization of indicators--

“What characteristics (indicators) are important to program quality in your field?”

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Program Faculty Quality Most Impt Indicator (Mark 4)

Top 2 Indicators

Number of publications per faculty member

Number of citations per publication

Racial/ethnic diversity of the student population

Avg. # of Ph.D.s granted over last 4 years

Gender diversity of program faculty

… … …

Direct Weights

Indicator 1= 0.2

Indicator 2= 0.0

Indicator 3= 0.1

Indicator 4= 0.1

Indicator 5= 0.2

…

Calculations

So how does NRC blend the two?STEP 2: Use faculty input to develop weights:– Method 2: A sample of faculty each rate a sample of 15

programs from which indicator weights are derived.

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Program #2: Yale University Economics

Some Facts About the Program:# of Ph.D.s 2001-2006: _____ Faculty % Female: _____Median Time to Degree: _____ Current Faculty List, etc.

Program #2: Yale University EconomicsProgram #2: Ivy University Economics

Program #1: Land Grant University Economics

Some Facts About the Program:# of Ph.D.s 2001-2006: XX Faculty % Female: YY%Median Time to Degree: Z.Z Current Faculty List, etc.

On a scale from 1 to 3, indicate your familiarity with this program?___ 1 (Little or none)___ 2 (Some)___ 3 (Considerable)

On a scale from 1 to 6, how would you rate this program?___ 1 (Not adequate for doc educ.)___ 2 (Marginal)___ 3 (Adequate___ 4 (Good)___ 5 (Strong)___ 6 (Distinguished)___ 9 (Don’t know well enough)

Regression-based

Weights

Ind. 1= 0.3

Ind. 2= 0.04

Ind. 3= 0.2

Ind. 4= 0.15

…

PrincipleComponents& Regression

So how does NRC blend the two?STEP 3: Combine both sets of indicator weights and apply them to the raw data:

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Direct Weights

Ind. 1= 0.3

…

Regression-based

Weights

Ind. 1= 0.2

…

Combined Weights

Ind. 1= 0.25

…

DATAIndicatorValue

# publications/fac 1.07

# citations/article 1.17

Median GRE 746

Gender diversity 44%

Time to degree 5.67

…

X= Rating

RANKEDLIST

1. Ivy Univ (98)

2. Random Univ (94)

3. Private Univ (91)

4. Land Grant U (88)

5. Univ of State (87)

…

So how does NRC blend the two?STEP 4: Repeat steps 500 times for each field

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A) Randomly draw ½ of faculty

“important characteristics”

surveys

C) Randomly draw ½ of faculty

program rating surveys

B) Calculate “direct” weights

D) Compute “regression-

based” weights

E) Combine weights

F) Repeat (A) – (E) 500 times to develop 500 sets of weights for each field

G) Randomly perturb institutions’ program data 500 times*

H) Use each pair of iterations (1 perturbation of data (G) + 1 set of weights (F)) to rate programs and

prepare 500 ranked lists

I) Toss out the lowest 125 and highest 125 rankings for each

program and present the remaining range of rankings

*For more information on the perturbation of program data, see pp. 50-1 in the NRC Methodology Report

Section 4

4. Presenting & Using the Results

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What are the indicators?Program Faculty Quality Student Characteristics Program Characteristics

# of publications per faculty member

Median GRE of entering students

Avg. # Ph.D.s granted in past 5 years

# of citations per faculty member

% students receiving full financial support

% entering students who complete

Receipt of extramural grants for research

% students with portable fellowships

Time to degree

Involvement in interdisciplinary work

Racial/ethnic diversity of student population

Placement of students after grad

Racial/ethnic diversity of the program faculty

Gender diversity of student population

% students with individual work space

Gender diversity of the program faculty

High % of international students

% of health insurance premiums covered

Reception of peers of a faculty member’s work as measured by honors/awards

# of student support activities provided

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What will the results look like?• TABLE 1: Program values for each indicator plus

overall summary statistics for the field

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RU Econ All Economics Programs (n=117)

Indicator Value Min 25th %tile

75th %tile

Max Std. Dev.

# publications/fac 1.07 .049 .369 .655 1.257 .246

# citations/article 1.17 .153 .684 1.771 5.485 1.002

Median GRE 746 353 740 790 800 55

% female students 44% 0% 28.6% 42.9% 76.9% 12%

% female faculty 12.5% 0% 10.5% 21.1% 66.7% 9.9%

Time to degree 5.67 3 5 6 8 .8

…

What will the results look like?• TABLE 2: Indicators and indicator weights – one

standard deviation above and below the mean of the 500 weights produced for each indicator through the iterative process (and a locally calculated mean)

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Indicator Minus 1 SD Plus 1 SD Calculated Mean

# publications/fac 0.130 0.134 0.132

# citations/article 0.294 0.267 0.2805

Median GRE 0.091 0.089 0.09

% female students -0.029 -0.043 -0.036

% female faculty n.s.* n.s.*

Time to degree -0.026 -0.031 -0.0285

…

*n.s. in a cell means the coefficient was not significantly different from 0 at the p=.05 level.

What will the results look like?• TABLE 3: Range of rankings for RU’s Economics

program alongside other programs, overall and dimensional rankings

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Institution Overall Research Activity

Diversity of Acad Environ.

Student Supp/Outcomes

25th %tile

75th %tile

25th 75th 25th 75th 25th 75th

Ivy Univ 30 36 31 32 37 41 28 31

Univ of State 45 54 40 42 42 50 45 46

Random Univ 45 56 38 42 47 51 43 47

Private Univ 48 57 41 42 40 47 45 49

Land Grant U 55 63 59 64 48 50 54 61

Total # of ranked programs = 117

What will the results look like?• TABLE 4: Range of rankings for all RU’s programs

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Program Overall Research Activity

Diversity of Acad Environ.

Student Supp/Out

comes

1995 NRC

Ranking

2009 USNWR Ranking

25th 75th 25th 75th 25th 75th 25th 75th

Linguistics 45 56 … 40 38Material Sciences and Engineering

25 26 24 24

Mathematics 21 23 23 25Mechanical Engineering

32 36 33 33

Neuroscience 34 35 34 35Operations Research

54 56 56 53

Philosophy 43 44 … 44 43

Q&AQ

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For more information…• The full NRC Methodology Report

http://www.nap.edu/catalog.php?record_id=12676

• Helpful NRC Frequently Asked Questions Page

http://sites.nationalacademies.org/pga/Resdoc/PGA_051962

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