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Defining, Counting and Understanding Faculty in 

the United States:

Strengths and Limitations of Current Higher Education Data

Caren Arbeit, RTI

KC Culver, University of Alabama

1
Who are the faculty in the United States?

o The academic workforce: Teaching, research, and/or community outreach

o “It is essential to understand who they are; what they do; and whether, 

how, and why the nation’s faculty are changing” (NSOPF, 1999)

o Three challenges to reaching this understanding using existing data:

• Definitions

• Coverage (institutional and individual)

• Changing nature of faculty workforce

2
National Study of Postsecondary 

Faculty (NSOPF)

o Collected by National Center for 

Education Statistics (NCES) in

• 1987-88 

• 1992–93

• 1998–99 and 

• 2003–04

3
About NSOPF

o Purpose

• Provide a national profile of part-time and full-time faculty and instructional staff 

working in public and private not-for-profit two-year and four-year institutions in 

the US

• Data on faculty’s backgrounds, responsibilities, workloads, salaries, benefits, and 

attitudes

o Definition of faculty

• Emphasis on instructional staff, regardless of faculty status

• Inclusive of full-time and part-time instructors

• NSOPF-88 limited to instructional faculty; later iterations expanded to include 

non-instructional faculty (researchers, administrators) and instructional staff 

without faculty status

4
NSOPF Challenges: Definitions and Coverage

o Accuracy in faculty counts provided in institutional questionnaire and in 

faculty lists

• Across cycles, 18 – 58 percent of responding institutions had discrepancies of 

10% or more between questionnaire and lists

o List data were used to stratify and sample faculty; In NSOPF-99, 

race/ethnicity and/or sex were missing for 35% of faculty on lists

o Differences between NSOPF and IPEDS definitions created challenges for 

count verification, weighting, etc.

5
NSOPF Challenges: Capturing Part-Time Faculty

o “Providing a complete and accurate list of part-time faculty is, for most 

institutions, the most difficult part of the NSOPF data request” (NCES, 

2006)

• Discrepancies between counts and lists higher among part-time faculty

o Contacting: 32% of part-time faculty required intensive training

o Survey completions: 11% lower among part-time faculty

6
7

Federal surveys that include faculty

Institutional level o Integrated Postsecondary Education 

Data System (IPEDS)

Individual Level o Survey of Doctorate Recipients (SDR) o Early Career Doctorates Survey (ECDS) o National Survey of College Graduates 

(NSCG)

o American Community Survey (ACS) o Current Population Survey (CPS)
IPEDS Definitions and Related Challenges

o Definitions of faculty

• Aligned with SOC Postsecondary Teachers: “Staff generally regarded by 

institutions as faculty are not only instructional staff, but can be research staff 

and public service staff as well”

• “Adjunct instructional staff”: instructional staff paid on a course-by-course basis

- Disconnected from part-time employment status and course loads; may be carrying fulltime equivalent course loads (or more)

o Designations based on institutional definitions

• Part-time or full-time

• Faculty status

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IPEDS Faculty Status

9

1%

23%

0

100,000

200,000

300,000

400,000

500,000

600,000

Full Time Part Time

Instructional Staff

Without faculty status

With faculty status

78%

71%

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

Full Time Part Time

Research Staff

Without faculty status

With faculty status

63%

62%

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

Full Time Part Time

Public Service Staff

Without faculty status

With faculty status
IPEDS Challenges: Coverage and Part-Time Faculty

o Capturing research staff

• Bergom and colleagues (2010) interviewed research faculty at 11 institutions; 5 

of those did not report any research staff in IPEDS data

o Capturing part-time faculty

• Institutions increasingly outsource some instruction; these instructors are not 

included in IPEDS (Powers, 2019)

• Snapshot of part-time faculty in Fall may not reflect institutional usage across a 

12-month period (Powers, 2019); No data on part-time non-tenure-track faculty 

hires (Jaquette & Curs, 2022)

• Part-time faculty teaching at multiple institutions may be counted multiple times

• Salary information is not captured for part-time faculty

10
Individual-level Surveys of Doctorates

o Survey of Doctorate Recipients (SDR)—NCSES 

• Survey of science and engineering doctorates from U.S. Institutions

• Conducted every 2-years; new longitudinal panel

• Includes items on rank, tenure, institution type, work activities, salary, hours

o Early Career Doctorates Survey (ECDS)—NCSES 

• Survey of doctorate (and equivalent) holders who earned degrees in the 10 

years prior to the reference date

• Two-stage sample of academic institutions with science, engineering or health 

master’s or doctoral degrees

• Included SDR items as well as items on work-life balance, mentoring, and 

benefits

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ECDS and SDR Estimates of Faculty

12

Survey

Selected 

characteristic

All 

position 

types

Faculty

All Faculty

Tenured 

faculty

Tenuretrack 

faculty

Non-tenure 

track 

faculty 

with rank

Other 

faculty, no 

rank or 

tenure

ECDS 2017

Population N 186,700 125,600 27,300 58,500 13,000 26,800

Percent na 100 21.7 46.6 10.4 21.3

Median Salary $68,000 $73,000 $80,000 $78,000 $73,000 $45,000

SDR 2019

Population N 1,149,000 380,000 211,000 63,000 68,000 38,000

Percent na 100 55.5 16.6 17.9 10.0

Median Salary $118,000 $95,000 $109,000 $84,000 $82,000 $60,000
Non-Federal Institution-Level Surveys and Challenges

o Surveys of faculty compensation, benefits, and roles

• AAUP’s Faculty Compensation Survey (900 institutions; data on 370,000 fulltime and 90,000 part-time faculty) 

• CUPA-HR’s Faculty Survey (1,300 institutions; data on more than 260,000 fulltime faculty)

o Challenges

• Population of interest varies (e.g., research faculty, community outreach faculty, 

postdoctoral scholars, primarily administrative faculty)

• Two-year institutions underrepresented (12-14% of sample; 25% of institutions 

nationally)

• Part-time faculty data lacking

13
Federal Individual-level Labor Market Surveys

o National Survey of College Graduates (NSCG)—NCSES

• 92,537 individuals with a Bachelor’s degree or higher in 2019

• Education history, employment, occupation, industry

o American Community Survey (ACS)—Census 

• Annual 1% sample of the population

• Asks about educational attainment, employment, occupation, industry

o Current Population Survey (CPS)—BLS 

• Monthly survey with rotation groups

• Monthly topical modules focused on economic topics

14
Non-Federal Individual-level Surveys and Challenges

o Regular surveys of faculty perspectives and behaviors

• COACHE; Harvard University (2012-2017: 180 institutions, 43,000 faculty)

• FSSE; Indiana University (2021: 75 four-year institutions, 9,000 faculty and 

GTAs)

• HERI Faculty Survey; UCLA (2016: 157 institutions, 25,910 full-time 

undergraduate faculty)

• CCFSSE; University of Texas Austin (2022: 105 institutions, ~10,000 faculty)

o Challenges

• Significant participation costs; institutional self-selection

• Varying faculty populations of interest

• Data is not publicly available

15
Challenges Across Data Sources

o Varying definitions of faculty and populations of interest make it difficult or 

impossible to compare data across sources

o Marginalized faculty (part-time, contingent, research, community outreach) 

generally under-represented

o Institution-level data cannot capture faculty perceptions and behaviors

o Faculty-level data is dependent on the purpose of study and respondents

16
Takeaways and Next Steps

o Important to clearly define terms and classification criteria

o A comprehensive study of faculty requires both institution-level and facultylevel data

o The FACE Project (Faculty, Academic Careers, and Environments)

• Developing proof of concept and infrastructure for a nationally representative 

survey of faculty

• Conducting focus groups with institutional data providers to guide definitions and 

processes

• Funded by the National Science Foundation

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Let’s continue the conversation!

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www.faceonfaculty.org

Twitter: @faceonfaculty

@kcculver

@carenarbeit

kc.culver@ua.edu

carbeit@rti.org