Key Technology: Internet of Things.
The National
Intelligence Council (2008) informs the term Internet of Things (IOT) originally
referred to the possibility of discovering information about a tagged object by
browsing an Internet address or database entry that corresponds to a particular
RFID. Today’s visionaries have seized on the term and expanded its meaning to include
the general idea of things or everyday objects that are readable, recognizable,
locatable, addressable, and/or controllable via the Internet - whether via
RFID, wireless LAN, wide-area network, or other means. Everyday objects
includes not only the electronic devices we encounter every day, and not only
the products of higher technological development such as vehicles and
equipment, but things that we do not ordinarily think of as electronic at
all—such as food, clothing, and shelter; materials, parts, and sub-assemblies;
commodities and luxury items; landmarks, boundaries, and monuments; and all the
miscellany of commerce and culture.
Chui,
Löffler, and Roberts (2011) believe the IOT has great promise, but there are challenging forces that must be tackled so the concept can gain real traction and become more
widely embraced. Early adopters will need to prove that the new sensor-driven
business models create superior value. Industrial groups and governmental
regulators will have to address data privacy and data security, particularly
for uses that touch on sensitive consumer information. Legal liability
frameworks for the bad decisions of automated systems will have to be
established by public and private stakeholders. The financial cost of technology must
fall to levels that will spark widespread use. Technological standards for networking that support them must evolve to the point where data can flow freely
among sensors, computers, and actuators. Software to aggregate and analyze
data, as well as graphic display techniques, must improve to the point where
huge volumes of data can be absorbed by human decision makers or synthesized to
guide automated systems more appropriately. Individually, these challenges
could take years to resolve – together, decades.
The 2012 New
Media Consortium (NMC) and Educause Report ‘Higher Education Edition’ pegged
the IOT time-to-adoption as being 4 to 5 years. I find the estimate to be
overly optimistic not only for the challenges already mentioned, but for the
lukewarm adoption of IPv6 - the protocol key to facilitating the expansion of
the Internet. Gartner Research provides an estimate of 5 to 10 years
(Brockmeier 2011).
The estimate
is part of their ‘Hype Cycle’ for technologies. To explain, the Hype Cycle tracks
technologies through a lifecycle that begins with a technology trigger through
the plateau of productivity. The idea is that companies can use the assessments
to decide whether to invest in specific technologies (Gartner 2011). With all
the challenges and the extended expectation of adoption by mainstream, I
estimate the time-to-adoption to more like 10 to 15 years. Why? The IOT will birth
disruptions of technology all the way to the end.
Key Trend: The NMC and Educause take the
position that the abundance of resources and relationships made easily
accessible via the Internet is increasingly challenging educators to revisit
our roles. Further, institutions must consider the unique value that each adds
to a world in which information is everywhere. In such a world, sense-making
and the ability to assess the credibility of information are paramount.
Mentoring and preparing students for the world in which they will live and work
is again at the forefront. They conclude that universities have always been
seen as the gold standard for educational credentialing, but emerging
certification programs from other sources are eroding the value of that mission
daily. Conversely, I see where certification programs from other sources
augment – even innovate the mission of educators.
Jones (1995)
first acknowledged that learning occurred in other formats and outside the
context of traditional education yet stood little chance of being recognized.
Ensuring that individuals can have the learning they have achieved recognized by
employers and institutions of higher learning was critical to addressing the
issue of limited resources. Further, leaders inside and outside higher
education had high hopes that technology would keep higher education from
becoming less isolated while being tailored to the needs of the individual.
Instead, some observers of higher education expressed concern that industrial
certification could eventually challenge traditional degree programs and the
educational path of choice for discerning knowledge workers.
The
observers concerns proved a bit overblown as community colleges served as the
ideal educational institution to address both education and certification. How?
Flynn (2000) explained that community colleges satisfied the demand for
credentialed education and training that falls outside the traditional college
model and calendar for completion. Moreover, they didn’t hold the stigma of the
ivory tower portrayed by higher traditional education –all while providing the
necessary tools for entry into a 4-yr institution, if desired. Through
partnerships, community colleges promoted certifications with the support of
industry and business. The outcomes were tangible with either path – an A.A.
degree or a professional certification. This formula was quickly adopted by the
for-profit universities and has steadily made its way through the traditional
universities and colleges.
Does the modified Delphi process that
they used to develop it affect the results?
In their
article ‘The Delphi Method for Graduate Research’, researchers Hartman, Krahn
and Skulmoski conclude that when adapting a modified Delphi process, there
needs to be a balance between validity and innovation. Their literature also
suggests that the absence of triangulation by other research processes means
there was no departure from the traditional Delphi method needing results
corroboration. Based on this observation, one can assert the modified Delphi process
employed by the NMC did not influence the outcome of the results – it merely
streamlined it.
Typical Delphi Process
 |
NMC Modified Delphi
Process
References
Brockmeier, J. (August 2011). Gartner
Adds Big Data, Gamification, and Internet of Things to Its Hype Cycle.
Retrieved July 25, 2012 from http://www.readwriteweb.com/-enterprise/-2011/08/gartner-adds-big-data-gamifica.php
Chui,M., Löffler, M. & Roberts, R.
(January 2011). The Internet of Things. Retrieved July 23, 2012 from http://www.paristechreview.com/2011/01/28/the-internet-of-things/
Flynn, W. (2002). More Than a Matter
of Degree--Credentialing, Certification and Community Colleges. Retrieved July
27, 2012 from http://www.eric.ed.gov/PDFS/ED467853.pdf
Gartner (2011). Gartner's 2011 Hype
Cycle Special Report Evaluates the Maturity of 1,900 Technologies. Retrieved
July 26, 2012 from http://www.gartner.com/-it/page.jsp-?id=1763814
Jones, D. (November 1995). Higher Education
and High Technology: A Case for Joint Action. Retrieved July 26, 2012 from http://www.eric.ed.gov/PDFS/ED400721.pdf
National Intelligence Council (NIC).
(November 2008). Global Trends 2025: A Transformed World. Retrieved July 23,
2012 from http://www.dni.gov/nic-/PDF_GIF_confreports/-disruptivetech/-appendix_F.pdf
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