Back to Basics and the Next Big Thing
The other day I watched a lecture presentation that was held in the beginning
of the 2001 academic year. Selected speakers invited to present on my campus
are captured, with permission, on streaming media for later viewing. The practice
is increasingly common and for good reason—we can’t attend all the
events we’d like to, but we’d prefer not to miss out entirely. Others
of us find hearing or seeing things again improves our understanding of the
material. I’m a little slow so this helps me a lot.
I listened to the narrative of a faculty member, whom for the sake of privacy,
we’ll call Alex. He had mortgaged his career on teaching with technology
and found himself nearly bankrupted by the experience. Before going on, let
me tell the good news: he recovered and received tenure, an outcome that anyone
who has seen this fellow teach would have expected. Still, it was touch and
go since he hadn’t written a major opus in his discipline and instead had
invested considerable effort into exploring new teaching approaches with technology.
In the recurring nightmare of sixth year faculty, things didn’t go well,
almost on cue.
His students were among his harshest critics. They blamed him for their frustration
at having assignments crunched by bit-stream bandits who stole files that were
submitted, or simply when the system wouldn’t open the work that was planned
for a given seminar. It wasn’t a pretty picture. His course evaluations
suffered accordingly. But, as a truly committed teacher, Alex set about exploring
why things fell apart, and what he intended the students to learn. He found
his love of teaching was now eclipsed by his newly kindled interest in student
learning. What he found was that many of the goals he had for his students were
really implicit. The goals emerged from readings and assignments, but their
emergence depended heavily on expert knowledge he wanted them to learn but which
they didn’t have.
Too often our use of technology can stand apart from our consideration of
good teaching. John Seely Brown, in The Social Life of Information (Harvard
Business School Press, 2000), suggests that knowledge is a composite of knowing
what (explicit knowledge), knowing how (tacit knowledge), and knowing people
and their practices. Higher education has focused nearly exclusively on knowing
what. We are only starting to get at the active learning approaches that lead
more toward knowing how.
It is useful to think about using technologies that would help emphasize these
attributes of learning. The vast majority of technology tools are focused on
learning “what”—tools that organize learning assets, usually
in text forms—for presentation or easy retrieval. There is still lots of
room for improvement, especially around tagging and indexing these materials.
And while these tools assemble information, that is only part of the learning
landscape. As Diana Laurillard has written, “It is as absurd to try and
solve the problems of education by giving people access to information as it
would be to solve the housing problem by giving people access to bricks.”
Nevertheless, putting content online is the most developed area of instructional
software.
Learning “how,” ah, that’s another story. Learning how implies
engagement, visualization, and active participation. It is the area where technology
is just getting to the point at which we can begin to work effectively. Work
going on in the humanities in the use of rich media for narrative expression,
inter-cultural communication, and interpretation of literature is one of the
areas in the forefront. These activities demand infrastructure capable of handling
large amounts of information, processing ability, and storage. This is more
than just “large pipes,” or high-bandwidth networks. Instead, it is
in the province of middleware between applications and the fiber-optic cables
connecting the network nodes.
Much of technological progress revolves around making the complex invisible
so that the next layer of development can proceed. You don’t think twice
about clicking on a hyperlink to bring a Web page to your screen, but the actions
that must be successfully executed to accomplish this are remarkable. When we
had to hand-code pages to present nicely formatted HTML, we were reminded of
one small slice of that complexity. Now we click “save to HTML” and
go on with our creative writing.
Grid Computing: The Next Big Thing
The next big thing to transform the Internet is likely to come from work going
on with the grid. The grid is an infrastructure that enables flexible, secure,
coordinated resource sharing among dynamic collections of people, institutions,
and resources.
It may be useful to recall that the birth of the Web came from a desire to
share research papers among large numbers of particle physicists doing “big
science” at CERN, the Swiss research center. Tim Berners-Lee’s vision
has changed all our lives. In the world of international science, its impact
has been staggering. Recognizing this, the Joint Information Systems Council
(JISC), the UK analog of the National Science Foundation, has embarked on a
£98 million project called the Core e-Science Programme, managed by the
Engineering and Physical Science Research Council (EPSRC) on behalf of the UK
Research Councils. The e-Science project proposes to connect scientists with
expensive remote facilities, teraflop computers, and information resources stored
in dedicated databases. Add to these resources higher level services such as
workflow, transactions, data mining, and knowledge discovery, and you begin
to glimpse what’s envisioned. The grid is the architecture proposed to
make this a reality.
What kinds of research are we talking about? Everything from particle physics
(what g'es around comes around) to basic medical investigation. For example,
our understanding of even basic human physiology remains terribly limited. We
don’t know how multiple parameters interact over time in fundamental processes
like heart rate, blood pressure, and other cardiovascular indicators. Imagine
if 100,000 people volunteered to wear real-time monitoring devices so that their
daily metabolic functions were recorded and analyzed in real time. The volume
of data is enormous but that’s just the beginning. We would want to compare
how the data relate to the activities of the people as they went about their
daily lives.
In the end, predicting the likelihood of an impending physical
problem becomes a potential reality. Just like the work underway to provide
predictive intervention for the replacement of computing hardware, you can imagine
high risk heart patients wearing proactive monitors that page them to head for
a cardiac care unit because the data indicate a potential problem in the next
24 hours. Today it may seem like science fiction, but with research using the
grid, it’s emerging into possible science fact.
This may seem far a field from the classroom. How far it is remains to be seen
of course, but there are people working today on applying the potential of the
grid to learning management or virtual learning environments. Better descriptions
about teaching processes and the learning objects needed, along with work on
metadata for educational objects, are underway. So stay tuned for more about
the “next big thing” in future columns.
References
Laurillard, D. The Changing University. 1996.
http://itech1.c'e.uga.edu/itforum/paper13/paper13.html
Metadata for Education Group
www.ukoln.ac.uk/metadata/education/regproj
Grid Links
Research Councils UK
www.research-councils.ac.uk
UKERNA News
www.ja.net/documents/UKERNA_News/2001/december/UKERNA_News17.html#15
