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

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