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Recently published NSF agenda “Fostering Learning in the Networked World” deserves attention for at least several reasons. First, it puts the learning sciences at the centre of the cyberlearning agenda. Second, it takes the opportunities to improve education by harnessing and using scientific and learning data seriously.

The Two Data Deluges: Opportunities and Threats

"Among the greatest benefits—and challenges— of cyberinfrastructure is the deluge of scientific data <….> Today’s highly instrumented science and engineering research is generating data at far greater rates and volumes than ever before possible. In addition, as more human communication takes place in the networked world for education, commerce, and social activity, an extensive digital trace is being created, a deluge of behavioral data. These data are extremely valuable for modeling human activity and for tailoring responses to the individual…” (24)

Will this open a door for eResearch in education and for education?

Harness the Deluge of Scientific Data

“There is very little past expertise in this area, as the data deluge is a relatively recent phenomenon. We need to invent ways to teach and train the next generation as we go. Yet this is an area with enormous potential. The need for such skills cuts across all fields of science and much of society. This also raises an interesting question along a strategic continuum: where should our training focus? Should we solve these huge interdisciplinary problems by encouraging large interdisciplinary teams to work together, or should we increase the versatility of individuals and provide an ever-faster rate of retraining?” (43)

Harness the Deluge of Learning Data

“A large number of cyberlearning projects have been accumulating vast amounts of student data in a variety of domains and grade levels. These include interaction data from online courses, intelligent tutoring systems, virtual labs, and online assessments in subject matter <…>. In the future, we expect increasing amounts of learner data available from formal and informal learning activities in the context of online chat, cell phones, games, and even toys. <….> Machine learning, psychometric, and cognitive modeling methods are increasingly being combined to discover improved cognitive-affective-psychometric models of student achievement and engagement through embedded assessment in cyberlearning systems. Open-learning data repositories are beginning to emerge, along with new computational techniques for analyzing such data. A new field of educational data mining is emerging <….> NSF should encourage data contributions, data use, new algorithm development, and, most important, common standards for data storage so both data and algorithm sharing are facilitated.” (43)


NSF (2008) Fostering Learning in the Networked World: The Cyberlearning Opportunity and Challenge. A 21st Century Agenda for the National Science Foundation. Report of the NSF Task Force on Cyberlearning. June 24, 2008.