Blog
Post #2 Cost Disease and Digital Technologies
What is cost disease and how does it
relate to higher education?
Baumol
and Bowen (1966) coined the phrase “cost disease” when they wrote about the economics
of the performing arts. For example, the same number of performers and staff
are required to put on a play at a Shakespeare festival. If the festival is in a country where there
is high labor productivity then actors’ wages need to be higher to attract the
same talent. Ticket prices need to be
higher to pay for the higher wages.
This
“cost disease” also impacts higher education, another service industry with
slow labor productivity and also that has to compete for a highly educated
workforce with other industries that can produce cheaper goods. Therefore, in
higher education, “rapidly rising service prices follow from the fact that
service industries’ costs are rising more rapidly than the costs of producing
most goods” (Archibald & Feldman, 2011, p. 39). Like the increase in ticket prices at the Shakespeare
festival, the increase in higher education cost is passed to the student.
There
are other reasons why the cost of higher
education has increased. At the same time that states are reducing allocations
for higher education, administrators are under pressure to increase
institutional rankings and performance with higher competition. Graves (2005)
wrote that administrators face a catch-22 in the form of declining
institutional revenues, while increasing competitive funding for need-based
financial aid and merit-based tuition discounts.
Robert Zemsky, a long-standing expert
on American higher education, stated “US higher education is in a mess. We
really can’t bring our costs under control; we still don’t have the completion
rates that we ought to have; we aren’t taking advantage of the power of new
technology; and universities are losing their standing as enterprises of value
and worth. These are the same issues that have been around for 40 years” (Parr,
2013).
Why
is digital technology an issue?
Bowen
(2012) wrote about cost disease, technology, and how they relate to higher
education. “In terms of ‘mismanagement,’ the introduction of new technologies
usually forces reexamination of the assumptions that underpin less productive
processes.” They give a telling example concerning the introduction of
electricity in manufacturing: “[Early on,] factories simply swapped large
electric motors for waterwheels and steam engines but retained inefficient
belt-and-pulley systems to transmit power from the central power source. Real
productivity gains came only after manufacturers realized that many small
motors distributed throughout a factory could generate power where and when it
was needed” (New England Journal of Medicine, cited in Bowen, 2012, p. 5).
In
much the same way as the introduction of electricity in manufacturing, the
introduction of new technologies in higher education is ever-changing and still
evolving in efficiency gains. Several documents that I read outlined many
issues concerning digital management in higher education. They included privacy
concerns associated with cloud networking, influx of corporate-academic
partnerships, the continued increase in online learning, the globalization of
higher education through distance learning, the need for instructional design
for multi-media lecture halls and flipped classrooms, and faculty perceptions
and integration of technology.
Many
of these areas are intertwined. Each area is important and could be the topic
of a blog by itself. However, this blog will focus on three key digital
technology areas that impact cost disease in higher education: students’ use of
mobile devices for academic purposes, data security, and digital flexibility.
How can we manage digital technology in
higher education?
The
management of digital technology in higher education is at a crossroads.
Technology is viewed as instrumental, both as a source of positive campus
impact and as a disruptive innovation (Economist, 2008). Institutional leaders
have digital technology decisions to make. They must “decide whether to resist
the change or get out in front of it” (Savenije, 2013).
The
decisions have to do with funding that can impact the core values of the
institution and the purpose of the university in relation to student outcomes. Lev
Gonick, Vice President for Information Technology Services and Chief
Information Officer at Case Western Reserve University, gave the keynote
address at the 2013 Campus Technology conference. Gonick said “we on our campus
are significantly mired in conversations that are arcane to our students and,
in the future, put us in peril in terms of spending precious institutional
resources on things that truly, truly at this point have been commoditized and
students are more and more simply ignoring.”
The pivotal question is how management of digital resources can help
higher education institutions remain relevant to and create value for
contemporary students.
Mobile Devices
Duggan
(2013) reported that 91 percent of American adults own a cell phone, of which
65 percent are smartphones, and 74 percent participate in social networks.
Therefore, it is imperative that IT leaders continue to explore and understand
mobile and social behaviors to digitally engage and position higher education
institutions to remain relevant to students.
“Students believe technology
makes them more productive” (Oblinger, 2012, p. 12). They want expedient access
to student and academic resources in a practical and portable way. Students use
their mobile devices for communication, entertainment, navigation,
organization, and increasingly, delivery of their learning experiences. They
expect real-time delivery of applications that create value and system support.
Therefore, the proliferation of mobile devices has implications for how we
interact with students at all interaction points -- the admissions process,
student engagement, and throughout the academic process.
The term, BYOD, or
bring-your-own-device, is now widely-used in campus IT departments and
publications to symbolize the growing popularity of mobile technologies by
college students. “Although students
still rate laptops (85 percent) as the most important devices to their academic
success, the importance of mobile devices such as tablets (45 percent),
smartphones (37 percent), and e-book readers (31 percent) is noticeably on the
rise” (Chen & Denovelles, 2013). The rate of using smartphones and tablets
for educational purposes has doubled in just one year to over 65 percent of
college students (Chen & Denovelles, 2013).
But, are colleges and
universities ready for the challenges of an increasingly mobile campus? In his 2013 keynote address, Gonick did not
think so. He said, “We are still struggling on many of our campuses on whether
or not we should be PC or Mac” and these conversations “are of no consequence
because the young people, who are currently in our university [and] college
systems, have moved on.” Students enroll
and expect to have connectivity and be able to conveniently navigate through
their collegiate experiences via their mobile devices. Yet, just 17 percent of the IT leaders
surveyed rated their current mobile services as “excellent” (Campus Computing,
2014). Clearly, there is room for
improvement.
Although colleges and
universities are lagging behind the smartphone and tablet consumer market,
forward-thinking IT leaders continue to prioritize the implementation and
support of mobile technologies, services, and apps in their campus strategic
plans. “Across sectors, public universities lead the movement: 99 percent will
be up on mobile apps by the end of the current academic year, followed by 95
percent of private universities, 92 percent of public four-year colleges, and 77
percent of community colleges and 73 percent of private four-year institutions”
(Campus Computing, 2014).
Data
Security and Digital Flexibility
Two
dilemmas that IT leaders face from the influx of mobile devices on campus are
data security and decisions surrounding the flexibility of mobile applications
and operating systems. Grajek (2015)
stated that “bring-your-own-device (BYOD), digitalization, and associated
technologies and opportunities are changing the nature of user support and
appropriate security policies” (p. 16). Most collegiate IT systems were built
before the complexities of mobile technologies and cloud computing. The servers, networks, and computer equipment
were owned by the institution; and therefore, everything about the data could
be controlled.
“Today, faculty, staff, and students expect to use
institutional systems and to access, transmit, and store data anytime and
anywhere using a wide variety of personal and work devices and applications”
(Grajek, 2015, p. 31). Institutions must
push accountability for security to users. Currie (2012) noted “We’re
essentially talking about granting access to unprecedented amounts of private
data to our least security-savvy constituents who will use the data on the
least secure and controllable devices we’ve ever had on campus” (p. 174).
Therefore,
digital technology leaders will need to make deliberate policy decisions
regarding access, use, and storage of data.
Currie (2012) stated that “the next wave of mobile software development
will enable “containerization,” which will allow IT departments to turn off
certain elements of applications that might jeopardize security” (p. 174). If a device becomes lost or stolen, a data
security mechanism may be built in to keep the data safe. “IT organizations
must have a strategy to allow access to adequate, secure, and appropriate data
for more entities in the higher education ecosystem, while also taking the
utmost care for the privacy of individuals” (Grajek, 2015, p. 38)
Another
concern is how to handle the support and functionality of multiple operating
systems that students utilize, such as those used on the iPhone, Android,
Blackberry, or among many other operating systems. Currie (2012) stated that “schools are
finding wisdom in building mobile applications that are flexible enough to work
on a variety of device types and that don’t require downloading” and noted that
there are a number of standard frameworks “built to simplify the creation of
mobile applications that are device agnostic” (p. 173). Website developers now have access to HTML5
which changes the appearance of the website to fit the screen to whatever
device is being used such as a smartphone, tablet, or laptop. As outlined in Currie’s (2012) report, this
digital technology is also demonstrated on mobility platforms such as UCLA’s
Mobile Web Framework, CampusEAI’s myCampus, and Kuali Foundation’s KME
(p.173).
Digital
technology leaders continue to look for solutions to provide personal and
powerful results for optimal delivery of user interface options, services and
software applications, file storage and security, and support for the entire
campus community. Currie stated “Since students brought the mobile revolution
to us, they should be a critical part of helping us understand how to
incorporate this new paradigm into the education process” (p. 177). Student perspectives on how they are using
mobile technology to enhance their academic outcomes will add significant
insight to the decisions facing IT leaders.
What is a solution for technology productivity
in an age of shrinking budgets?
A business model for campus
digital technology transformation must be a priority for IT leaders who wish to
provide value to contemporary college students. Colleges
and universities must fund the wide variety of integration points of this
diverse environment within a seemingly ever-shrinking budget. When
multiple initiatives are a priority, what is a reasonable guideline for IT
leaders when managing their strategic plans and budgets? The IT funding model suggested by the
Educause Core Data Service (2013) study (as cited by Grajek, 2015) was 76
percent of central IT’s budget spent on running the institution, 15 percent
spent on growth, and 9 percent spent on transformation.
The
underlying question is whether or not higher education brick and mortar
campuses will continue to exist if digital technologies continue in their
growth patterns. Higher education
thought leaders agree, albeit at varying levels, that campuses will still exist
even as digital technologies become more vigorous and service-oriented (University
of the future, 2012; Grajek, 2015; Gonick, 2013). However, there is a caveat.
“Campuses will still exist as places of teaching and learning, research,
community engagement, and varied forms of student experience -- assuming
universities can deliver a rich, on-campus experience” (University of the
future, 2012, p. 9). This on-campus experience incorporates not only
face-to-face activities but also meets the students’ digital expectations.
Therefore,
universities and colleges must continue to explore and design digital
technologies for mobile devices, social networking, and cloud computing to
create functionality that keeps in line with how students, faculty, and
administrators interact with each other, engage with the institution, and
learn. Grajek (2015) stated that the “success and perhaps even the survival of
higher education are more dependent than ever on technology” (p.15). Careful
management of these initiatives by IT leaders in collaboration with
academicians, instructional designers, administrators, and students will ensure
that higher education institutions continue to be relevant in the future.
References
Archibald, R.B.,
& Feldman, D.H. (2011). Why does college cost so much? New York: Oxford University Press.
Baumol,
W., and Bowen, W.G. (1966). Performing
arts: The economic dilemma. New York: Twentieth Century Fund.
Bowen,
W.G. (2012). The ‘cost disease’ in higher education: Is technology the answer? Retrieved from http://r.search.yahoo.com/_ylt=AwrT6V2pVRxWGFEAOWwnnIlQ;_ylu=X3oDMTE0dnEyMGpvBGNvbG8DZ3ExBHBvcwM1BHZ0aWQDRkZYVUk0MV8xBHNlYwNzcg--/RV=2/RE=1444726313/RO=10/RU=http%3a%2f%2fithaka.org%2fsites%2fdefault%2ffiles%2ffiles%2fITHAKA-TheCostDiseaseinHigherEducation.pdf/RK=0/RS=cWXVCloMqjprmMmFADo1MoIPS4s-
Campus
Computing (2014). The 2014 national survey of computing and information
technology in US higher education. Retrieved from
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Chen, B., & Denovelles, A. (2013). Exploring students' mobile learning practices in higher education. Retrieved from http://www.educause.edu/ero/article/exploring-students-mobile-learning-practices-higher-education
Currie,
C. (2012). Impact of mobile computing. Planning For Higher Education, 41(1),
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Duggan, M. (2013). Cell phone activities 2013. Retrieved
from http://www.pewinternet.org/2013/09/19/cell-phone-activities-2013/
Gonick,
L. (2013, July). The revolution has just begun: Envisioning the future of IT
in higher education. Opening
keynote address presented at 2013 Campus Technology Conference, Boston, MA. Retrieved from http://events.mediasite.com/Mediasite/Catalog/Full/8f468b665de54501b797f995ad81434 021
Grajek,
S. (2015). Top 10 IT issues, 2015:
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Graves,W. H. (2005). Improving institutional performance through
IT-enabled innovation. Educause Review, 40(6), 78–99. Retrieved
from http://er.educause.edu/articles/2005/1/improving-institutional-performance-through-itenabled-innovation
New
Media Consortium, Economist Intelligence Unit (2008). The future of higher education: How technology will shape learning. Retrieved
from http://www.nmc.org/pdf/Future-of-Higher-Ed-(NMC).pdf
Oblinger, D. G. (2012). IT as a
game changer. In D. G. Oblinger (Ed.), Game changers: Education and
information technologies (pp. 37–52). Louisville, CO: Educause. Retrieved
from http://net.educause.edu/ir/library/pdf/pub72033.pdf
Parr, C. (2013). Robert Zemsky’s
solution for US problems. Retrieved from https://www.timeshighereducation.com/news/robert-zemskys-solution-for-us-problems/2006778.article
Savenije,
D. (2013). 12 tech trends higher
education cannot afford to ignore. Retrieved from http://www.educationdive.com/news/12-tech-trends-higher-education-cannot-afford-to-ignore/156188/