Unleash the power of networked learning

Excerpt from article by Martha Stone Wiske, Harvard Graduate School of Education in Harvard Business Review

Amplify’d from blogs.hbr.org
Unleashing the Power of Networked Learning

What’s different is that the top-down, center-out approach to traditional education is dramatically diminished. Learner-generated, informal interactions, short messages, and nonverbal media are the norm in these networked learning situations. No longer are we worried about “warming up” the online environment — it’s plenty hot! No longer are we pondering the advantages of deliberate, reflective, collaborative knowledge construction in a formal threaded discussion forum. We are tapping into a cacophony of rapid fire exchange that is more like scrappy conversation bursts at a party than orderly discourse of academic knowledge building.

How do we conceive and harness the power of networked learning in this context? Well, that’s the new question this year. Clearly networked learning can be powerful: just ask Hosni Mubarak. The current generation of students in high school, college, and graduate school are figuring this out. Their teachers need to ask themselves, “How do we work with our learners to foster the critical thinking, complex communication, and collaborative construction of warranted knowledge that we believe it is our responsibility to do?” What is clear is that we won’t be in charge the way we used to be or thought we were.

Read more at blogs.hbr.org



Sematic web and information processing

Qwiki looks like a very interesting platform. It’s like Wikipedia in that it is like an encyclopedia of general knowledge, only instead of the knowledge being constructed primarily by contributors, it is created by machines, pulling all these little bits and pieces of content from other spots on the web. It does this on the fly using semantic web technologies. There is a way that users can participate, by suggesting sources of information that might improve a Qwiki, but the heavy lifting is primarily done by machines. And it looks very pretty. The UI is slick.

In taking a look at Qwiki, I came across this blog post from Gregory Roekens in which he connects semantic web technologies with a theory of knowledge creation and information processing called mental space theory, which, in turn, is based on something called a DIKW (data, information, knowledge and wisdom) hierarchy. DIKW illustrates a hierarchical relationship in that data and information lead to knowledge, which leads to wisdom. I haven’t come across this term or theory before, but it is intriguing.

Amplify’d from tell.posterous.com

Qwiki is one of those emerging platform leveraging the semantic web. I often used the Ackoff’s allocation of mental space theory to explain the importance of Semantic Web and its huge potential. This theory is based on the DIKW hierarchy.

In a nutshell and using the diagrams below, our brain is using 40% of mental space to process data into information, a further 30% to process information into knowledge, 20% to process knowledge into Wisdom and only the remaining 10% is used to process Wisdom into Vision (see diagram 1).

In his work Scott Carpenter explains that thanks to data-handling technology (think excel spreadsheet, charts and dashboard) it allows the human cognitive energy to shift upward and produce information out of data (see diagram 2). Without these technologies the cognitive is locked down by mundane and time consuming effort to process the data into information.

What’s really exciting in Scott’s theory is that with the Semantic Web and its semantic processing power cognitive allocation can shift to Wisdom and Vision with the machine effectively delivering the Knowledge (see diagram 3).

Read more at tell.posterous.com

Qwiki via Stephen Downes