Understanding the productivity of faculty members in higher education

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nt. J. Management in Education, Vol. 12, No. 2, 2018
Copyright © 2018 Inderscience Enterprises Ltd.
Understanding the productivity of faculty members
in higher education
Julie A. Delello*
College of Education and Psychology,
The University of Texas at Tyler,
3900 University Blvd.,
Tyler, TX 75799, USA
Email: jdelello@uttyler.edu
*Corresponding author
Rochell R. McWhorter
College of Business and Technology,
The University of Texas at Tyler,
3900 University Blvd.,
Tyler, TX 75799, USA
Email: rmcwhorter@uttyler.edu
Shelly L. Marmion
College of Education and Psychology,
The University of Texas at Tyler,
3900 University Blvd.,
Tyler, TX 75799, USA
Email: smarmion@uttyler.edu
Abstract: With the price of rising tuition and mounting student debts in the
USA, there continues to be much debate as to whether faculty members at
universities work hard enough and whether that work benefits students. This
article discusses key findings of a mixed-methods case study reflecting the
breadth of work-related activities engaged in by university faculty at one
regional university in Texas transitioning towards a greater focus on research.
Contrary to popular press, it was found that full-time faculty members at
all ranks worked more hours per week than the national average and two-thirds
of those were spent in teaching related activities. The authors caution
those entities pushing for large overhauls in higher education to abandon
misinformation regarding faculty work roles and urge administrators to include
very knowledgeable and concerned faculties in such discussions.
Keywords: faculty performance; faculty accountability; higher education;
faculty scholarship; work-life balance; faculty workload.
Reference to this paper should be made as follows: Delello, J.A.,
McWhorter, R.R. and Marmion, S.L. (2018) ‘Understanding the productivity
of faculty members in higher education’, Int. J. Management in Education,
Vol. 12, No. 2, pp.154–178.

Understanding the productivity of faculty members in higher education 155
Biographical notes: Julie A. Delello is an Associate Professor in STEM
education in the College of Education and Psychology at The University of
Texas at Tyler. She holds a PhD in Curriculum and Instruction with a
specialisation in science and technology from Texas A&M University. Her
research interests include augmented and virtual reality, gamification, visual
literacy, and social media for learning.
Rochell R. McWhorter is an Associate Professor of Human Resource
Development in the College of Business and Technology at The University of
Texas at Tyler. She holds a PhD from Texas A&M University. Her research
interests include Virtual HRD, professional branding, virtual scenario planning,
the Internet of Everything, real-time group meetings, cybersecurity for HRD,
and online service-learning.
Shelly L. Marmion is a Professor of Psychology in the College of Education
and Psychology at the University of Texas at Tyler. Her research interests
include effects of emotion on cognition, effects of trauma on adult functioning,
societal change to reduce violence towards women, and gender and social
cognition.
1 Introduction
Across the USA, new higher education reforms seem generally to be driven by declining
state funding and college affordability initiatives (Fryar and Carlson, 2014). In a State of
the Union address, US President Barack Obama endorsed college value and affordability,
creating a new “College Scorecard” that allows individuals to “get the most bang for
[their] educational buck” (Duncan, 2013, para. 5). Obama (2012) asserted, “So let me put
colleges and universities on notice: If you can’t stop tuition from going up, the funding
you get from taxpayers will go down. Higher education (HE) can’t be a luxury – it is an
economic imperative that every family in America should be able to afford” (para. 41).
The Department of Education (DOE, 2016a) recently requested 30 million dollars to
conduct research and analyse performance data of institutions of HE, specifically in areas
of access, completion, and affordability. Hunter Rawlings (2012), President of the
Association of American Universities noted that Americans want a complete justification
of their tuition expenses and a ready return on their investment.
With the price of rising tuition and mounting student debt, faculty productivity has
been heavily scrutinised (Hamilton, 2011; Wexler, 2016). Ludwig (2011) stated, “With
budget cuts tightening around HE’s neck, reformers who want to shake up the ivory
tower are gaining a foothold with changes that would favour teaching over research”
(para. 3). In this debate, productivity is achieved when a faculty member generates
sufficient funding, either through research grants or tuition from larger class sizes to
equal their own salary. Included in proposed reform measures are radical modifications
to the role of faculty members, which push them to meet difficult productivity measures
in research and teaching. As Rich (2013) articulated, “The emerging environment of HE
is more turbulent, more competitive, and more threatening than was the case only a few
decades ago” (p.262). Pressures to boost graduation rates and more efficiently prepare
students for a changing workforce has placed significant pressures on HE and faculty
who work there (Nadeem, 2013).

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Given the nationwide trend of shrinking education budgets, it is important to
understand the myriad of responsibilities today’s faculty members face, especially as
“some university systems choose to cope with leaner funding through cost savings –
perhaps at the expense of educational quality – by thinning their number of faculty or
combining programs” (Weismann, 2013, para. 4). Furthermore, regional institutions,
which have historically focused on teaching, have been under increasing pressure to do
more research, publish, and bring in additional university funding (Miller and Seldin,
2014). As greater scrutiny is being placed on efficient use of time – it is vital that we
understand (a) what is the time investment by faculty members in a variety of work-
related activities at a transitioning regional university? And, (b) what are the work
products and outcomes for faculty members at a transitioning regional university?
In this paper, we will look at ways faculty at a regional university in Texas spend
their time and whether they are vital and efficient or wasteful and in need of reform. We
will first present a review of relevant literature followed by methods of the study, data
collection including presentation of a case study, findings, discussion, implications and
conclusions.
2 Relevant literature
Claims against US higher education have suggested that faculty members are
overcompensated for minimal teaching loads or inefficient teaching schedules (Levy,
2012; O’Donnell, 2011a). One reason tuition costs have skyrocketed is escalated faculty
salaries (AAUP, 2012a). Some have even suggested that faculty salaries have continued
to increase but faculty productivity has not (Surowiecki, 2011; Wexler, 2016). For
example, Wisconsin Governor Scott Walker stated, “Maybe it’s time for faculty and staff
to start thinking about teaching more classes and doing more work” (Belkin and Peters,
2015). A Washington Post article echoed this claim, stating, “though faculty salaries now
mirror those of most upper-middle-class Americans working 40 hours for 50 weeks, they
continue to pay for teaching time of nine to 15 hours per week for 30 weeks” (Levy,
2012, para. 5). Although such a characterisation misrepresents the work-life and
contributions of professors, they have spurred policy makers to target full-time faculty
salaries and productivity levels at both two and four year public institutions in reducing
HE costs (AAUP, 2012b).
Disparity today between public perceptions and the reality of the average professor’s
job could not be greater. Even very well-educated citizens tend to perceive professors as
“coddled elites holding lucrative sinecures, protected by an outmoded practice of tenure”
(Mattson, 2011); however, despite years of advanced education, most faculty members in
HE earn less than $60,000 annually (Nelson, 2010). According to College and University
Professional Association for Human Resources (CUPA-HR) 2015–2016 Administrators
in HE Salary Survey data, for Master’s degree-granting institutions in the South central
USA, average salary for all combined ranks is $68,512 (College and University
Professional Association for Human Resources, 2016). In contrast, those that are
comparably educated, earning advanced degrees such as MBAs, law degrees, or other
professional degrees, often earn over $100,000 annually (Ross, 2016).

Understanding the productivity of faculty members in higher education 157
While full-time faculty salaries have actually decreased 0.12% since the recession
(AAUP, 2016), recent studies highlight tuition increases have come with exponential
growth of university administration. According to the AAUP, there has been an
expansion of administrative positions (Curtis and Thornton, 2014). For instance, from
1987 to 2012, The New England Center for Investigative Reporting noted that on
average, 87 administrators and professional employees were added to HE campuses each
day. While faculty salaries have declined, senior administrators have received double-
digit increases (Marcus, 2014). According to an annual compensation survey by the
Chronicle of Higher Education, in 2014 the typical college president earned over
$400,000, almost 3.8 times as the average full-time professor at large universities
(Bothwell, 2015). For example, the President of The University of Texas at Austin
receives an annual salary of $750,000 (Kambhampati, 2015) and Texas A&M’s President
has a current base salary of $1 million plus benefits (Woodhouse, 2015). These executive
salaries contribute to increases in tuition prices on many campuses (Curtis and Thornton,
2014; Wexler, 2016). In The Fall of the Faculty, Ginsberg (2011) noted that many HE
administrators and staff members have no faculty experience and too little work to keep
them occupied. Thus, while administrator salaries and positions have rapidly increased,
faculty salaries have remained flat.
3 Teaching performance
At present, there are over 1.4 million faculty members in the USA who teach, research,
and perform service (Knapp et al., 2012), with over 25,000 employed by Texas public
universities (The Texas Higher Education Coordinating Board, THECB, 2015). Teaching
performance as described by Boyer (1990) is a dynamic endeavour driving scholarship
and educating students. Yet, Berrett (2012) acknowledged that across higher education
(HE), faculty members spend less time in classrooms than in the past and have little
support to improve their teaching efforts. Legislators and the general public are failing to
comprehend why ten or twelve hours spent weekly in classrooms is only one aspect of
teaching, due to their “lack of awareness of the hard work and the serious study that
undergirds good teaching” (Boyer, 1990, p.23). According to Musick (2011), many
responsibilities that accompany teaching such as mentoring students, coordinating
internships and study abroad programs go unmeasured, thus, inadequately measuring
faculty productivity.
4 Research productivity
According to Carey (2012), “The struggles of those workers are well known but worth
repeating: Great college teachers work in a system of professional values and
institutional incentives that systematically rewards research over teaching” (para. 4).
According to Jaeger and Thornton (2006), faculty members are forced to exhibit market-
like behaviours to secure competitive funds in order to support continued research costs.
This need for corporate or governmental funding has substantially “weakened the fabric
of faculty life on research-university campuses” (Wilson, 2013, para. 5) and corporate

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shift may create an institution “where autonomy and academic freedom begin to
evaporate” (Park, 2012, p.92). The push for more funding has also created a state of flux
for smaller teaching institutes. Kelsky (2016) remarked that in the “arms race” for
prestige, endowment money, and grants, they [institutions] may seek to boost research
productivity expectations among faculty (with little of the institutional support for that
productivity that is common at research institutions)” (para. 12).
As universities embrace entrepreneurship, the importance of scholarly research may
be in question. Berdahl (2009), former President of the Association of American
Universities pointed out that the value of academic research is an amalgamation of
scholarship and academic freedom:
The strength and quality of American research universities are derived from
many sources: fundamentally from the freedom in which they operate, and
which they, in turn, propagate; from the breadth and interaction of the multiple
disciplines…from the partnership between universities and the federal
government built on a competitive environment driven by merit; and from the
linkage of education, research, and scholarship (p.1).
The importance of academic freedom has been formally recognised in the USA since
1940 when representatives of the AAUP and the Association of American Colleges and
Universities (AACU) established a set of principles known as the 1940 Statement of
Principles on Academic Freedom and Tenure (AAUP, 2006). These principles protect
rights of faculty members to carry out classroom teaching, research, and service
consistent with their academic disciplines, areas of expertise, and personal interests. Such
academic freedom and values necessary to the free flow of ideas is the lifeblood of
worldwide scholarship, with implications for the advancement of knowledge and
invention. Academic freedom and accountability in all areas of the professoriate remains
the subject of much public concern and debate (AACU, 2006).
Faculty members are uncertain about the future of higher education (Selingo, 2013).
Research has documented that, contrary to public conjecture, faculty members at all
ranks are working long hours and face enormous institutional pressures (Delello et al.,
2014; Eagan and Garvey, 2015). Further, a survey conducted by the Cooperative
Institutional Research Program (CIRP) at the Higher Education Research Institute
(HERI) in 2010–2011 illustrated that self-imposed high expectations, lack of personal
time, institutional budget cuts, and administrative red-tape generated the highest levels of
stress among faculty (Hurtado et al., 2012). As a direct result of these proposed HE
reform initiatives, faculty morale may become problematic (Hamilton, 2011). There
continues to be much debate on how to increase accountability and in turn, reinvent HE.
Jalbert (2009) noted that faculty need time and resources to be good teachers; however,
research and publications have seemingly become the top priority, even in institutions
previously oriented towards teaching. According to Drnevich et al. (2010) institutions
should strongly invest in the quality of research and education.
Boyer (1990) stated, “It’s futile to talk about improving the quality of teaching if, in
the end, faculty are not given recognition for the time they spend with students” (p.6).
Lechuga and Lechuga (2012) noted that although excellent teaching is important, the
push for meritorious research may trigger faculty to lose the motivation for superior
instruction. Reasons for failing faculty retention are stress, lack of promotion, or overall
dislike for their current working conditions (Berrett, 2012; Delello et al., 2014).

Understanding the productivity of faculty members in higher education 159
5 Texas pushes reforms
Texas is the second largest state in the USA with 38 public universities, with most being
regional universities (THECB, 2010) that “offer a broad scope of undergraduate degrees
and some master’s degree programs but few, if any, doctoral programs” (U.S. News &
World Report, 2016, para. 1). According to Perna et al. (2012), Texas still lags behind
other states in terms of HE performance as the ratio of degrees awarded to cost of
education that continues to escalate. In order to target rapid population growth and
measure productivity, The THCEB adopted the state’s HE plan Closing the Gaps by
2015 (CTG) which focused on “increasing college enrollment, raising number of degrees
awarded, pushing the state’s colleges and universities up in national rankings, and luring
more federal research dollars” (Perna et al., 2012, p.1). The plan addressed four critical
areas in HE: “participation, success, excellence, and research” (THECB, 2010, p.4). The
plan challenged institutions of HE to make conscious efforts to ensure needs of both
traditional and non-traditional students. According to THECB (2015), the plan was
somewhat successful in terms of increasing college enrolment, bringing in more federal
research dollars and boosting academic reputations of institutions.
Additional proposals have emerged from state-level stakeholders in Texas calling for
more accountability and transparency in teaching and research. Based on Texas Public
Policy Foundation’s 2011 Seven Step Framework, these HE reforms result from state
budgetary cuts and burgeoning student debt (Hamilton, 2011; Zavattaro and Garrett,
2013). In response, the state’s two largest HE systems, Texas A&M University and The
University of Texas, established an accountability practice of publishing faculty
performance data online (June, 2011). Further, a recent UT System chancellor publicised
a plan entitled The Framework for Advancing Excellence to meet demands of a changing
HE landscape and increased accountability (Cigarroa, 2011), results of which remain to
be seen.
Behind these reform initiatives is the assumption that faculty members do not
earn their salaries (AAUP, 2015). For instance, O’Donnell (2011a) recommended that
lawmakers take immediate measures to remove unproductive faculty members
(“coasters” and “dodgers”, see O’Donnell, 2011b) whose combined research funding
and/or tuition monies generated by their classes fail to support their own salaries. He
estimated these “unproductive” faculty members comprise over 76% of all faculty at The
University of Texas and suggested that this supposed lack of productivity was the key
reason for soaring costs in higher education (HE). Daley (2011) wrote one of numerous
criticisms of O’Donnell’s (2011a, 2011b) methods, pointing out that no distinction was
drawn between tenure and non-tenure track faculty, nor between chemists and poets as if
each faculty member is “producing the same widget-like research product” (Daley, 2011,
para. 8).
Annual evaluations of faculty is a routine management process in HE (Collan et al.,
2014). According to the Texas Public Policy Foundation (TPPF) (2011), the first reform
goal of institutions of HE is to measure teaching efficiency and effectiveness. Currently,
teaching performance is measured by average student satisfaction ratings and course
enrolment figures. However, student evaluations are often influenced by a variety of
student-held biases based on characteristics of the instructor and course, including
personality, gender, age, teaching style, and grades-awarded (Sprinkle, 2008), as well as
students’ perceived difficulty of course content (Constand and Pace, 2014). Finney and
Finney (2010) noted that when students perceive themselves as consumers, they may
have negative attitudes and feel a sense of entitlement.

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There is also movement in the Texas State Legislature aimed at curbing grade
inflation by moving to an “authentic” or “honest” transcript. The bill would require
institutions of HE to list individual students’ grades and course averages (Lindsay, 2013).
With student debt at national highs and with low graduation rates plaguing HE, grade
transparency may not be the best solution. Resulting grade deflation may hurt students
trying to compete nationally for jobs with other institutions who have not initiated such
policies (Foderaro, 2010). These so called “honest” transcripts may also negatively
impact professors, whose careers rely in part on good student evaluations for tenure and
promotion (The Daily Texan Editorial Board, 2014; Huemer, 1998).
According to proposed Texas reforms, a distinction between teaching and research
faculty would become the standard. Faculty who conduct research would be paid based
on sponsored research dollars they attract from government, business, and private donors
(TPPF, 2011). Institutions of HE are already in the process of moving toward academic
capitalism and institutional entrepreneurship, causing faculty members to spend more
time on “research activities closely tied to corporate or government funding over
teaching and service opportunities” (Park, 2012, p.94). McLendon and Hearn (2013)
reported that legislators based in Texas were even considering performance-based
funding for up to 25% of the state’s funding for HE. According to Brix and Jakobsen
(2015), there is little consistency in the way such business modelling and organisational
practice is done in academia.
6 Theoretical framework
Profound changes are occurring in HE as faculty struggle to balance their teaching,
research, and service with their personal lives (Delello et al., 2014; McClure, 2016).
However, much examination of faculty workloads to date has concentrated on large
universities which have a significant commitment to research with somewhat reduced
teaching loads. But many smaller regional universities find themselves in the midst of
transitioning from a more teaching oriented identity to one attempting to straddle dual
goals related to research and teaching.
In terms of productivity, there are many factors that may motivate faculty members
including those such as tenure and promotion, external funding opportunities, and
publications (Mamiseishvili and Rosser, 2011). Expectancy theory or VIE theory states
that individuals’ efforts are based upon their desire for a reward (Valence), the likelihood
of obtaining the reward (Expectancy), and their belief that they can achieve or obtain the
reward (Instrumentality) (Vroom, 1964). The Expectancy Theory argues that “people
make decisions among alternative plans of behaviour based on their perceptions
[expectancies] of the degree to which a given behaviour will lead to desired outcomes”
(Mathibe, 2008, p.8). In other words, individuals will engage in behaviours they value
and have interest in (Wood et al., 2015).
However, researchers have proposed that in order for faculty to be productive, there
must also be a balance between personal and work life domains (Bulger et al., 2007;
Delello et al., 2014). The central idea of work-life balance is based upon Nippert-Eng’s
(1996) framework of boundary theory, which proposed that individuals manage
boundaries between work and personal life through segmentation and/or integration of
domains.

Understanding the productivity of faculty members in higher education 161
Segmentation refers to keeping work and personal time separate in that “the mental
boundary between realms is clear and impregnable…with no conceptual overlap between
realms and their contents, there is no physical or temporal overlap between them either”
(Nippert-Eng, 1996, p.568). Integration refers to overlap between work and nonworking
time, in that, “no distinction exists between what belongs to home or work and when and
where they are engaged” (p.567). For many individuals, boundaries between integration
and separation fall on a continuum with neither being isolated entities (Ashforth et al.,
2000). Ashforth et al. (2000) indicated that blurring of boundaries creates a type of
permeability or “degree to which a role allows one to be physically located in the role’s
domain but psychologically and/or behaviourally involved in another role” (p.474).
Perhaps faculty are moving away from segmentation toward integration in order to
achieve the delicate balance between personal and work life (Walden, 2014).
Musick (2011), an Associate Dean at The University of Texas, stated “The university
data do not measure many thousands of hours that faculty work each year to publish and
keep abreast of their fields, supervise graduate and undergraduate students and their
research, and serve on committees” (para. 21). Conforming to the “do more, make less”
(Kreuter, 2013, para. 1) adage requires faculty members to either expand their
responsibilities by engaging in recruiting and promotion efforts to increase enrolment
numbers in the short-term or “rest on the whims of political and economic chance”
(para. 8). Mamiseishvili and Rosser (2011) remarked, “In the time of rising pressures and
demands placed on faculty work, it is important to examine how faculty productivity in
the core academic areas of research, teaching, and service relates to their job satisfaction”
(p.106).
No matter how well intentioned the calls for reform, suggested improvements may
produce a host of unintended consequences because they are based on false assumptions
regarding faculty roles, responsibilities, and contributions. Low pay and excessive work
conditions have left faculty members, particularly those at transitioning regional
universities, feeling disheartened and disillusioned with the task of educating students
(Delello et al., 2014).
The purpose of this study is to measure the breadth of activities engaged in by
regional university faculty in order to obtain an accurate picture of faculty contributions
to their university. This study may provide background needed to help retain faculty,
especially at smaller regional institutions that are transitioning from a focus on teaching
to a research emphasis. Therefore, the two specific research questions utilised in this
study were:
RQ 1: What is the time investment by faculty members in a variety of work-related
activities at a regional university?
RQ 2: What are the work products and outcomes for faculty members at a regional
university?
7 Methodology
We employed a single, descriptive case study design utilising a mixed method approach
(Yin, 2015). This study involved collection of data utilising a survey yielding
quantitative data and also qualitative data through open-ended response questions. The
major strength of a mixed method design is that it allows for research to develop

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comprehensively and completely by employing strengths of both quantitative and
qualitative measures (Mertens et al., 2010). Further, a case study utilising mixed methods
allows for data collection that builds “a comprehensive understanding of a case, the focus
of the study [with]…qualitative and quantitative data collection” (Fetters et al., 2013).
7.1 Context
The public institution in Texas which is the focus of this study has 75 degree programs,
almost half of which are graduate programs, 435 faculty members (43% tenure/tenure-
track), and over 7,400 students representing 47 nations, 48 states and 131 Texas counties
(The University of Texas System, 2013). Average yearly teaching load per full time
equivalent (FTE) was 23 credit hours. Estimated cost of an undergraduate degree at this
institution was just over $21,480, as compared to the state average of $42,504 and the
national average of $36,580 at other public four-year institutions nationwide (The
College Board, 2016; DOE, 2016b). This study represents an attempt to capture the
extent and range of workload duties at such a transitioning regional university within a
state in which the clamour for academic reform in resounding.
7.2 Data collection
All 293 full-time faculty members were contacted by their faculty senate president and
asked to respond to an online survey (Qualtrics.com) regarding their expenditures of
work-related time and resulting accomplishments. The survey instrument included
11 sliding-scale questions, five multiple-choice questions, 53 Likert-scale questions,
19 selection questions and two open-ended questions for written responses. The survey
was based on a faculty annual evaluation rubric used for a number of years by one of the
university’s colleges. Because faculty members often have differing roles and
responsibilities, we attempted to measure a full breadth of activities associated with these
roles using an instrument developed on this campus. After development, each question
was scrutinised and modified until we were satisfied that it was an accurate measure of
desired constructs, and coverage of each topic was adequate (see Walonick, 2011).
Beyond the successful use of the original instrument in annual review processes, using
familiar constructs often reported by faculty members, and completing a thorough
literature search helped to establish face and content validity (Walonick, 2011).
Institutional Review Board (IRB) approval was obtained and informed consent was
explained in emails in which participants were assured they could choose not to respond
to any or all questions without penalty.
Participants were asked in the survey to estimate their time expenditures (hours per
typical week) for the following: (1) work-related activities, (2) course preparation and
delivery, (3) grading and providing feedback, (4) mentoring, advising and other activities
to benefit students, (5) interacting directly with students, (6) responding to email,
(7) research activity, and (8) service-related activities. Two open-ended questions asked
participants to describe (1) other teaching activities that they were involved in, and
(2) other service and/or outreach activities. Participants were also asked to estimate
number of work-related hours spent during “vacation” or uncompensated time,
approximate out-of-pocket dollar amount in work-related expenditures, and hours spent
yearly in reporting and annual review processes. Participants were asked to indicate their
rank, tenure status, and whether they were employed on a nine or twelve-month contract.

Understanding the productivity of faculty members in higher education 163
Finally, participants were asked to provide data concerning their activities in areas of
teaching, research and service. Activity descriptors are included in Tables 3–5.
7.3 Demographics of survey participants
Data were collected from 140 professors, or almost 50% of those receiving the invitation
to participate which included all 293 full-time faculty at the participating university. Any
response rate below 100% opens the possibility of a non-response bias which may occur
whenever non-responders differ in important ways from responders, thus reducing
validity of data collected (Fosnacht et al., 2013). When a subset of non-responders were
queried as to their reason for non-response, replies (when received) were invariably about
a lack of time, a feeling shared by a similar subset of responders who took time anyway
because of perceived importance of the topic. Of those who responded to the survey,
20.7% were full Professors, 24.3% were Associate Professors, 27.1% were Assistant
Professors, and 26.4% were Instructors, a breakdown representative of the wider
institution. Furthermore, 40.7% were tenured faculty, 24.3% were tenure-track faculty,
and 32.9% were non-tenure track faculty. We interpreted the almost perfect match to
institutional breakdown of ranks as additional evidence that non-responders were not
different from responders. Additionally, we used t-tests and Chi-square tests to compare
responses on several key variables for those who responded to the initial email
solicitation to participate (N = 96) to those responding after the second and final prompt
(N = 43) and found no significant differences between these groups.
7.4 Data analysis
Descriptive statistics were computed for ratio-scaled variables. One-way ANOVA
designs were used to compare differing faculty ranks. Cross-tabs were run on the large
number of variables in which respondents either chose one of four phrases to describe
their level of involvement in various teaching and service activities, or indicated whether
or not they had engaged in or produced research activities or products.
Two open-ended survey questions were independently and systematically analysed
by two researchers of this study. To begin the qualitative analysis, responses were first
copied and pasted into a word processing document to create a transcript for analysis.
Then, researchers individually reviewed a copy of the transcript and iteratively developed
an initial list of themes found in the literature through an inductive and comparative
approach (Merriam and Tisdell, 2016), creating a coding document (similar to a
hierarchical codebook described by McQueen et al. 1998) that included rules for
inclusion (Lincoln and Guba, 1985; McQueen et al., 1998) for each theme accompanied
by participant extracts. Subsequently, each researcher independently performed category
construction by combining themes together through reflection and interpretation.
Intercoder agreement (McQueen et al., 1998, p.35) was reached as both researchers met
together and reviewed the two sets of coding documents and any inconsistencies were
further discussed and resolved. According to Merriam and Tisdell (2016), use of a team
of researchers to review data called “peer examination” (p.249) enhances confidence in
the findings.

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8 Findings
8.1 Total hours per week
Survey participants were asked to estimate the average number of hours spent working
each week. Average total time spent across all faculty ranks was 56 hours per week (SD
= 11.89). In addition to the 37.76 hours per week spent in teaching-related activities,
participants, on average, reported spending an average of 9.64 hours per week in
research-related activities (SD = 7.16), and 6.4 (SD = 5.27) hours per week in service-
related activities. Categories of teaching, research, and service activities do not add to
100% because some activities do not fit discretely into the three categories. That a sum of
the three primary task time estimates (teaching, research and service) fell short of
estimated total time spent each week by an average of more than 11 hours (M = 11.39,
SD = 14.31) was interpreted as indicating that these estimates were not inflated. Also,
because data was solicited by the Faculty Senate President rather than any part of
administration, we felt that over-reporting of times is at most very minimal. Although
courses are taught primarily in 15–16 week semesters, faculty members typically work
during vacation times, such as breaks between semesters. When asked the number of
hours worked during such “vacation times,” participants indicated an average of 16 hours
of work per week during such “off” periods.
8.2 Comparison of hours across faculty ranks
To test the common claim that professors who are protected by tenure often do less to
earn their salaries than those at earlier career stages (Trower, 2010), a one-way ANOVA
was computed to compare average number of hours in the work week across the four
ranks (instructors, assistant professors, associate professors, professors). See Table 1 for
mean hours per week reported by each rank and Table 2 for the ANOVA comparing
these means. Tukey’s HSD post hoc analyses indicated a significant difference in total
workweek time investment between lowest (non-tenure track instructors) and highest
ranks (tenured full professors), with professors having significantly longer work weeks
(M = 61.33, SD = 10.56) than instructors (M = 49.86, SD = 11.01), with F (3, 132) =
5.87, p = .001. The two intermediate ranks (assistant and associate professors) each
reported working an average of 57 hours per week, which did not differ significantly
from either instructors or professors. Approximately 12% of the variability in work hours
reported is accounted for by the rank of the individual. Thus, in terms of total hours of
work each week, professors are reporting more hours per week than any other rank.
Table 1 Means for total time reported as spent each week by ranks
Rank Mean Standard deviation Sample size
Professor 61.33 10.56 30
Associate Professor 56.85 12.58 34
Assistant Professor 56.75 10.97 36
Instructor or other Total 49.86 11.01 36
Total 55.96 11.91 136

Understanding the productivity of faculty members in higher education 165
Table 2 ANOVA for total time spent each week by each academic rank
Source df F η p
Total time 3 5.87 .118 .001
Within group error 132
Two other comparisons of reported time for specific tasks across ranks were significant
after Bonferroni adjustments. The estimate of total hours directly interacting with
students showed a significant difference, F (3, 132) = 4.05, p = .009, with full professors
reporting less interaction (M = 11.14) than instructors (M = 18.31), and with no other
ranks differing significantly. This may be due to the relatively larger teaching loads and
class sizes of instructors. Additionally, full professors estimated significantly more time
spent on work-related email by approximately four hours a week than any of the lower
ranks, which did not differ from one another, F (3, 132) = 4.17, p = .007. Two other one-
way comparisons across rank were significant at the .05 level, but should be interpreted
with caution because of the large number of analyses conducted. Professors reported
significantly more hours spent in service related activities by approximately 4 hours, than
did instructors, but did not differ significantly from other tenure ranks, F (3, 127) = 2.93,
p = .036. And last, professors reported working significantly more hours during vacation
periods by about 8 hours than did instructors but didn’t differ from other tenure ranks, F
(3, 125) = 3.16, p = 027.
8.3 Teaching activities
Expectations for research productivity in this institution have increased over the past
decade, and is combined with a typical teaching load of three courses, with faculty
members at all tenure levels spending approximately nine hours in the classroom weekly.
This is, however, a very small portion of time spent on teaching-related activities.
Faculty members responding to this survey reported spending an average of 17 hours per
week (SD = 7.74) in preparation and delivery of their courses. They reported spending
an additional 12.4 hours on average weekly (SD = 7.0) in grading assignments and
providing feedback to students. Additionally, they reported spending an average of
8.36 hours per week (SD = 6.2) in mentoring or advising students. There is likely some
overlap in time spent in some activities.
In the survey, professors were asked how much of a time investment (using a 4-pt
scale) they made in a variety of teaching-related activities. For each activity, they
responded whether it was something they “typically did not do,” was “an occasional
task,” a “moderately time consuming” part of their work week, or “a major time
investment”. These descriptors were used as markers on a 4-point scale assumed to be
ordinal in scaling. Data is interpreted simply as most to least frequently occurring
activities, providing no specific indication of actual time spent in each activity. The
percentage of professors indicating their level of involvement in a variety of teaching
activities is highlighted in Table 3. The greatest time investments reported, on average,
were increasing one’s own knowledge in content areas and updating courses accordingly,
planning multiple instruction strategies to facilitate learning, creating assessments of
learning and providing feedback to students, and having direct contact with students both
in classrooms and out.

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Table 3 Percentage of involvement in teaching activities
Teaching
activity
Do not
typically do %
Occasional
task %
Moderately time
consuming %
Major time
invested %
Updating courses 4.3 20.0 40.7 35.0
Increasing my knowledge base 7.0 12.9 47.9 34.3
Planning course instruction 3.6 45.0 10.0 41.5
Creating syllabi for courses 5.7 46.4 35.7 12.1
Assessment & feedback to students 4.3 5.7 35.0 55.0
Creating multiple instruction
strategies 5.7 15.0 45.7 33.6
Interaction with students 3.6 11.4 47.1 37.9
Curriculum planning 21.4 35.0 35.0 8.6
Professional development 11.4 50.7 33.6 4.3
Advising 19.3 23.6 32.9 24.3
Teach students not in my classes 28.6 42.1 21.4 7.9
Providing student opportunities 11.4 58.6 25.7 4.3
Student research sponsor 65.7 19.3 7.9 7.1
Assisting with student research 45.7 33.6 12.1 8.6
Thesis committee member 57.1 24.3 12.9 5.7
Chairing thesis committee 70.0 13.6 7.9 8.6
Student graduate committee 57.9 25.7 10.0 6.4
Comprehensive exams 56.4 22.9 17.9 2.9
Dissertation committee member 70.0 15.7 11.4 2.9
Chair dissertation committees 85.7 4.3 3.6 6.4
Department activities 12.9 59.3 22.9 5.0
Recommendation letters 9.3 55.7 27.9 7.1
Organising lecture events 55.0 31.4 7.9 5.7
Organising study abroad
opportunities 85.0 8.6 4.3 2.1
Field trips 77.9 17.1 4.3 .7
Organising workshops 46.4 40.7 11.4 1.4
Service teaching event 72.1 22.9 3.6 1.4
Co-curricular sponsorships 62.9 23.6 8.6 5.0
Organising research
conference/symposia 62.9 24.3 9.3 3.6
Maintaining accessibility 11.4 17.1 44.3 27.1
New course development 22.9 30.0 27.1 20.0
Teach new course preparation 15.7 21.4 24.3 38.6

Understanding the productivity of faculty members in higher education 167
8.4 Research activities
As with teaching, activities and pursuits related to research are numerous. Tenured and
tenure-track professors were asked to indicate whether they had engaged in various
research activities in the last year as described; and, whether they had produced any
research products typically measured as a sign of productivity. Research activities for the
past year most frequently reported by faculty included engaging in scholarly professional
development activities (83.5%), submitting a peer reviewed presentation proposal
(79.1%), and giving a scholarly presentation (72.5%). More than 60% had also
collaborated with peers outside their institution, submitted publications, had publications
accepted, served as journal reviewers, and/or engaged in data collection for an empirical
project (see Table 4 for percentages reporting each of 19 research activities).
Table 4 Percentage of involvement in research activities
Research activity % ‘yes’
I engaged in scholarly professional development activity 83.5
I submitted a proposal for a peer reviewed presentation to a professional
organisation 79.1
I gave one or more peer reviewed scholarly presentation(s) to a professional
audience 72.5
I have an established network of professional colleagues outside the university with
whom I interact regarding research. 69.2
I submitted research paper(s) or creative work for publication consideration to a
refereed journal or to the editor of a reviewed book or monograph 67.0
I served as a reviewer for books, journal articles, program proposals or (higher ed.)
student research competitions sponsored by a professional organisation 65.9
One or more of my articles were accepted for publication in the refereed or
nationally recognised professional journals 64.8
I produced tangible “work product” for an on-going research project 62.6
I engaged in data collection for an empirical study or project 60.4
I submitted a scholarly paper or creative work for publication consideration to the
non-refereed journal, newsletter, or self-publication/subsidy press 44.0
I gave a workshop, lecture, or demonstration based on my work to a community
audience 37.4
I submitted a grant proposal to a competitive funding agency 33.0
I gave an exhibition or performance of my work 30.8
I received a competitively funded grant from the regional, state, or national level 23.1
I received non-competitive funding for a research project 11.0
I was awarded a contract by a publisher as editor and/or author for a book 11.0
I received a funded intramural grant 9.9
I served as a reviewer or consultant for an external grant funding agency 9.9
A book was published for which I was the editor or author 8.8

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8.5 Service activities
Professors were asked how much of a time investment (using a 4-pt scale) they made in a
variety of service-related activities. As with teaching activities, they were asked to
respond as to whether a service activity was something they “typically did not do,” was
“an occasional task,” a “moderately time consuming” part of their work week, or “a
major time investment”. Table 5 shows the percentage of professors who indicated
various levels of involvement with each service activity. The activities in which
the greatest time investments were made, on average, were service to committees
(particularly when chairing them), maintaining active roles in professional organisations,
participating in accreditation processes, and serving as a reviewer for various forms of
scholarship.
Table 5 Percentage of involvement in service activities
Service activities Do not
typically do %
Occasional
task %
Moderately time
consuming %
Major time
invested %
Serving on university, college, and
department committees; attending
meetings and carrying out assigned
tasks
3.7 23.1 51.5 21.6
Attending graduation and other
ceremonies 5.2 58.2 31.3 5.2
Providing professional expertise to
outside organisations or individuals
(paid or unpaid)
27.8 44.4 22.6 5.3
Serving as chair of a university,
college or department committees 34.3 23.1 29.9 12.7
Maintaining active membership in
professional service organisations 12.7 45.5 36.6 5.2
Serving on Faculty Senate 74.4 12.0 12.0 1.5
Serving as chairperson, director, or
coordinator of an academic
program
63.9 6.8 8.3 21.1
Serving as chairperson, director,
coordinator, or officer of a
professional organisation, civic
group or other service outreach
63.2 21.1 9.8 6.0
Serving as official advisor to a
student organisation 56.4 15.8 20.3 7.5
Engaging in extensive consultant
work in the community 57.9 29.3 9.0 3.8
Engaging in student recruitment
activities 23.3 51.1 22.6 3.0
Participating in Ad Hoc
committees 32.3 48.9 17.3 1.5
Serving in an executive office of
professional organisations 71.6 17.9 6.0 4.5

Understanding the productivity of faculty members in higher education 169
Table 5 Percentage of involvement in service activities (continued)
Service activities Do not
typically do %
Occasional
task %
Moderately time
consuming %
Major time
invested %
Serving as a reviewer of books,
journal articles, program proposals
or student research competitions
26.1 38.1 28.4 7.5
Donating a significant amount of
time in a professional capacity to
community and/or professional
service
40.3 37.3 15.7 6.7
Maintaining facilities such as labs
or studios 69.2 14.3 8.3 8.3
Securing funding for new
equipment or technology for use in
a lab, studio or classroom
72.4 11.9 9.7 6.0
Participating in accreditation
processes, including collecting,
Organising and reporting data
25.8 38.6 19.7 15.9
Developing recruitment materials
or participating in recruitment
events
40.2 29.4 18.2 2.3
Serving as mentor to new faculty 36.6 41.0 17.9 4.5
Finally, related to service, we asked participants the average amount of time spent
reporting yearly on activities for their annual review, promotions, accreditation
processes, etc. The mean number of hours reported spent on activity reports was 15.45
(SD = 12.96) yearly. Also, participants were asked to estimate average out-of-pocket
expenditures (such as books, software, equipment, travel to conferences, etc.) yearly. The
reported out-of-pocket expenditures per year averaged $1226.36 with considerable
variability (SD = 1153.11).
8.6 Open-ended questions
Data analysis reflected 8 themes comprising 2 categories (see Table 6) that emerged from
two open-ended questions regarding (1) other teaching activities; and, (2) other service
and/or outreach activities for which faculty were involved. Due to large quantities of data
collected, excerpts shown were selected to illustrate the themes course preparation,
work-related travel, community engagement, student support, professional advancement,
collecting accountability/accreditation data, personal time, and financial compensation.
Several faculty extracts corresponding to the two categories, Work-Related Activities and
Personal Time, are presented next.
Faculty reported spending time on course preparation as noted in the following
excerpt “I spend 48 hours a week in lecture prep with a minimum of 24 hours of prep
time.” Several faculty also reported that they spend numerous hours during their “off”
times working on course work, grading papers, and responding to students that creates
work-life balance issues as suggested in the following excerpt: “I spent hours each
weekend responding to students”. Faculty also noted spending time in community service
as stated in the comment, “[I] attend advisory committee meetings for all of the technical
programs at all of the surrounding junior colleges.”

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Table 6 Findings of open-ended survey questions with representative extracts
Category Name of
theme
Rule for
inclusion
Selected faculty member
extracts
1. Work-
related
activities Course preparation
Faculty members
reported course
preparation to be
time consuming
 Teaching online classes
requires an extensive
amount of time and
preparation
Work-related travel
Faculty members
reported time spent
traveling to various
learning sites
 I play an ambassador role
to the hospital leadership,
charge nurses and staff
nurses
Community
engagement
Faculty members
reported time
representing the
university in the
community
 I am university liaison
for [the Regional Service
Centre]
Student support
Faculty members
report time spent
mentoring and
supporting students
including handling
academic honesty
issues fairly
 Supervising students in
field assignments – on a
volunteer basis – not a
part of my assignment,
but because students ask
for the additional
feedback
Professional
advancement
Faculty members
reported spending time
on self-advancement in
their career including
tenure and promotion
expectations
 I am pursuing my
doctoral degree part-time
in order to advance
within the university
Collecting
accountability/
accreditation data
Faculty members
reported helping with
data collection and
reporting for
assessments for
certification and
accreditation
 Obtaining and processing
data for certification and
accreditation
2. Work-life
boundary
issues
Personal time
Faculty members
reported that they
spend time beyond
their allotted workday
in completing job-
related tasks
 I also have spent a lot of
my summer vacation
working on University
related activities…grant
reporting, and called
meetings where I was
expected to return to
campus
Financial
compensation
Faculty members
reported they did not
receive financial
compensations for
time worked
 Never compensated, not
even with time off during
the week

Understanding the productivity of faculty members in higher education 171
Furthermore, several faculty members noted their workloads were increased due to extra
time spent mentoring and working with students. For example, one faculty member
reported, “I am frequently asked to help doctoral student with statistics even if I am not
on their committee.” One faculty member even documented that supporting students was
difficult and created anxiety as expressed in the sentiment: “During the 5 hour hospital
time, I am responsible for 10 students and the care they are giving to their patients…can
be very scary since these students have never been in a hospital before.” These
representative extracts portray faculty members as over-extended, balancing both work
and life boundary challenges.
9 Discussion and implications
In this study, these findings are not surprising to those who are familiar with academic
life, but are in stark contrast to portrayals typically given by outsiders. Regardless of
rank, faculty members noted heavy workloads and long work hours with little
recompense. In fact, the study provided evidence that faculty surveyed worked more than
the national average of 55 hours a week (Schuster and Finkelstein, 2006) and also
worked during “vacation” periods. However, one of the underlying questions, resonating
from media and the public, is do faculty members teach enough? In this study,
participating faculty spent an average of more than 37 hours per week (66% of total) in
preparing for and teaching courses, grading, providing feedback, and mentoring students
(not including research and service). The number of hours was found to be more than
twice the time estimated by those who are publically urging sweeping changes in our
universities. Clearly in our sample, teaching and mentoring students was the primary
focus of the faculty.
When hired, tenure-track faculty members are expected to not only teach but engage
in research designed to add to the body of knowledge in their disciplines. In addition to
keeping up to date with the latest advances in their fields, faculty research serves the
public good through medical advances, technological innovation, enhanced productivity
in business and industry, and many other outcomes benefitting society (Daniel, 2011). An
additional reason for such scholarship is to expose students to the latest research in
various disciplines and help them to understand methods by which new discoveries are
made (Berdahl, 2009). Respondents to our survey varied widely, but indicated an average
time expenditure doing research related activities to be just under 10 hours a week. While
this is not a negligible amount, and is absolutely mandatory to earning and maintaining
tenure, it is important to note that it is only 17% of their average work week.
As for service, while not every faculty member engages in every form of service on a
regular basis, the breadth of tasks is again much larger than is typically recognised by
persons outside of academia, and comprised 11% of the work week. Universities, which
operate with a principle of shared governance, could not function without contributions
made by hard-working faculty members. Furthermore, as illustrated in the literature
(Berrett, 2012; Delello et al., 2014), these numerous job demands create an imbalance
between faculty members’ work- life and personal responsibilities.
As the academic landscape shifts towards corporatisation with increasing part-time
labour, a move away from tenure and academic freedom associated with it, and a
mentality where student “consumers” are given power to evaluate the “product,” student
learning outcomes will be negatively affected, despite efforts of a dedicated faculty, who

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typically are given little say in these matters. Schrecker (in Mattson, 2011) noted, “so
much of what passes for a discussion of HE today does not bring professors into the
conversation” (p.2). Based upon findings of this study, it can be concluded, as Barcan
(2014) noted, “Academics are expected to try, and all too often… serve as the human
glue striving to hold the fractured university together” (p.2). Perhaps, it is the faculty
members who are paying the high costs of an education (Benton, 2010).
Our results are consistent with recent studies showing that tenure does not lead to
lower long-term productivity (Nikolioudakis et al., 2015), and may even increase time
expenditures in some non-research areas (Antony and Hayden, 2009). While all four
ranks we studied reported working long hours each week, there were some differences,
particularly between instructors and full professors. Instructors reported more time spent
interacting with students, probably as a result of larger class sizes. But contrary to
popular press, tenured professors as a group were found to be the hardest-working of the
ranks in terms of work-week hours and breadth of activities, productivity which could be
lost with the shift away from tenure-track faculty – a shift increasingly being made in
higher education.
Faculty members are struggling to balance their time and several implications of this
study are evident. We found that faculty worked 56 hours per week, 16 hours more than a
full-time job showing a mischaracterisation in the amount of hours that faculty work as
compared to policy makers’ perceptions (AAUP, 2012b). Competitive compensation
needs to be considered across disciplines for all faculty as many faculty members are
paid less than salaried employees.
McNatt et al. (2007) noted that job satisfaction and organisational commitment is
impacted by compensation.
As the university transitions to a research-based institution, administrators must look
at workload expectations for faculty and create policies to help faculty manage their time.
These policies should focus on integrating personal and workload benefits. Incentives
such as wellness benefits, faculty and dependent tuition reimbursement, child care, and
activities for families should be considered. Strategies for balancing workload may
include smaller class sizes, library resources such as scholarly journals, research and
teaching assistants, grant writing support; and, offering required training and faculty
meetings in flexible delivery methods (i.e. virtual meetings). Furthermore, according to
Delello et al. (2014), “In order to attract and retain professors, institutions must create
flexible methods to achieve tenure and promotion, which may include hastening or
extending tenure review for faculty members based upon their individual needs” (p.55).
Ahmed et al. (2014) noted that high institutional support of teachers increased student
satisfaction and academic performance. In addition, a supportive environment which
includes open discussions, innovativeness, and flexibility has been linked to better
employee performance (Kamya et al., 2011). Conversely, Mathibe (2008) suggested that
when the organisation does not fulfil the needs of the employee, they may become
demotivated and unproductive.
10 Limitations
One limitation of this study was the survey questionnaire itself. Demographic data such
as gender and discipline were not collected in order to protect confidentiality of
faculty participants from relatively small departments; thus, we cannot determine

Understanding the productivity of faculty members in higher education 173
representativeness on these dimensions. Additionally, because the survey data was self-
reported, actual expenditures may differ somewhat from reported estimates. The survey
was also lengthy which may have resulted in a lack of participation from faculty
members or survey exhaustion.
Although high response and completion rates were obtained for this university, we do
not know the extent to which the data would generalise to other institutions, particularly
those differing in size and breadth of programs. The qualitative data was limited in scope
as we only asked two open-ended response questions making it difficult to comprehend
the full extent of emotions and behaviours from faculty members.
It should be noted that the university represented in this study has a limited number of
doctoral programs, which may have resulted in lower numbers in areas related to
graduate training (comprehensive exams, graduate committees) and graduate student
research (thesis and dissertation committees, research symposia, etc.) having been
reported. More comprehensive universities would show higher time expenditures in these
work categories. In spite of these limitations, this case study produced a thorough
representation of work activities and productivity of faculty members.
11 Future directions and conclusions
Additional studies might explore variations in workload among disciplines as suggested
by Jones (2011), and across differing types of universities. However, anecdotal evidence
suggests that the picture of university work-life found in this study can be replicated in
most HE institutions. It seems imperative that as universities are reshaped to meet the
challenges of greatly reduced state funding that their faculties be at the centre of those
processes of change. In what world does it make sense that expertise inherent in highly
trained faculty of such universities is excluded from decision making processes in favour
of state legislators and political players who, no matter how well intentioned, are basing
their proposals on a set of assumptions that are greatly flawed, and who have little
understanding of the consequences to students’ education likely to be unleashed by ill-
founded reforms? Future studies could include more extensive qualitative data gathering
techniques such as interviewing, focus groups, and observational time studies. Finally,
data should be gathered from campus and system-level administrators, to gather their
perceptions of the complex problem of how faculty members should spend their time.
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