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By JOHN SEELY BROWN

The digital age has vastly expanded people's access to all sorts of 
information and resources, including educational materials. The Internet 
has also fostered a new culture of sharing, one in which content is freely 
contributed and distributed with few restrictions. Indeed, the latest 
evolution of the Internet, Web 2.0, is creating a new kind of 
participatory medium that is ideal for encouraging multiple types of 
learning.

Web 2.0 has blurred the line between producers and consumers of content 
and has shifted attention from access to information toward access to 
other people. New kinds of online resources-- social-networking sites, 
blogs, wikis, and virtual communities-- have allowed people with common 
interests to meet, share ideas, and collaborate in innovative ways.

Two of those ways involve social learning, based on the premise that our 
understanding of content is socially constructed, through conversations 
about that content and through interactions around problems or actions. 
The focus is not so much on what we learn as on how we learn. In addition, 
social learning concerns not only "learning about" the subject matter but 
also "learning to be" full participants in the field. That involves 
acquiring the practices and norms of established practitioners in that 
field or acculturating into a community of practice, such as an 
open-source community, where you are required to assimilate the 
sensibilities and ways of seeing the world embodied within that community.

That culture of sharing and participation usually starts with the students 
themselves, as we see vividly in the complex, multiplayer game worlds and 
in the power of study groups, whether conducted face-to-face or virtually. 
Such a culture must also involve content. The Massachusetts Institute of 
Technology was a pioneer when it developed its OpenCourseWare project. 
Other universities quickly followed MIT's lead, and both the content and 
the means of accessing class materials and remixing and repurposing them 
for different audiences grew.

But it's time that we in higher education move beyond considering only 
content. We must begin to determine how that content can encompass 
multiple kinds of instructional or learning activities. It is, after all, 
the combination of things we do with content that creates learning 
platforms.

Two ways that technology can now transform our learning landscape are 
immersion and intelligent tutoring systems. Immersion is a concept that 
has received too little attention. Consider, for example, how every one of 
us has learned the immensely complex system that is our own native 
language: through immersion and desire. Immersion comes from being 
surrounded by others talking and conversing with us and is further 
encouraged by our deep desire to interact, to be understood, and to 
express our needs. Nearly everyone is a teacher for us-- albeit an 
informal teacher-- urging us to say new things, correcting us, and 
extending our vocabulary.

In today's high-tech, graphically rich world, we now have almost-limitless 
opportunities to teach and learn through immersion. We can build 
simulation models of cities, historic events, atomic structures, and 
biological and mechanical systems, to name just a few. Our challenge 
becomes how to share such vast simulations and databases so that other 
people can extend, remix, and recompose them, thus expanding both their 
scope and their reach.

For example, I still dream of a virtual human system that would allow me 
to explore any aspect of how our bodies-- organs, cells, membranes-- 
function. There are promising signs, but as yet we have no real framework 
for constructing and sharing modules of such a system. Perhaps we could 
entertain a vast and interconnected web of simulations. No one group can 
build it all, but many people could contribute, including students 
themselves.

Such richly visual, immersive, three-dimensional simulations will help 
students master complex topics. But they will not be enough. We need to 
augment those systems with computer-based intelligent tutors. Intelligent 
tutoring systems have a long history, stretching back to the 1970s, when 
our most-advanced systems required a million-dollar computer for each 
student. Now we have machines 10,000 times more powerful and much less 
expensive. That means that our past dreams for building intelligent 
tutoring systems that could offer open-ended learning under the skillful 
eye of a tutor, coach, or mentor are becoming realistic. Indeed, the work 
of Carnegie Mellon University and now its Open Learning Initiative-- which 
employs virtual labs, group experiments, and cognitive tutors-- have 
demonstrated the power and utility of such systems.

For decades we have worked to create better theories of learning and 
successful models of teaching, but no one pedagogical or technical 
approach will ensure that students are engaged and prepared. We need to be 
catholic in our point of view. We must think about how technology, 
content, and knowledge of learning and teaching can be creatively combined 
to enhance education and ignite students' passion, imagination, and desire 
to constantly learn about-- and make sense of-- the world around them. And 
we need to collect and share good models in which various professors' and 
students' experiences are commented on and tried out in new contexts.

How might we begin? How can we start gathering massive amounts of data 
about what is working and what is not, and why? Take the OpenCourseWare 
project. Millions of students may be using the material, but we need to 
ask what they are learning. What sequence of materials appears to be 
working best? Are there particular paragraphs or problems (in a problem 
set) that are routinely misinterpreted? How are test questions being 
misinterpreted? Are any systematic error patterns showing up? Those 
queries barely scratch the surface of the information that we need to 
collect.

We should extend our thinking around open education to include more of a 
Learning 2.0 perspective, based on Web 2.0, for two key reasons. The first 
turns on a question that John King, associate provost at the University of 
Michigan at Ann Arbor, first posed to me. He asked how many students I 
thought the university taught each year. I knew that it had approximately 
40,000 students, give or take a few thousand, so that was my answer. He 
responded that, while I had the enrollment right, 250,000 was closer to 
reality. What you forget, he told me, is that each year the incoming 
students bring their social networks with them. Those networks reach back 
into the students' communities and schools. Using the social-software and 
social-network tools of SMS, IM, Facebook, and MySpace, they extend the 
discussions, debates, bull sessions, and study groups that naturally arise 
on a campus to encompass that broader constituency-- thus amplifying the 
effect the university has across the country.

That phenomenon draws attention to the broader learning milieu or learning 
landscape we must consider, as well as to the extended forms of 
participation that the Internet offers. Those extended forms start to 
merge tools for doing research with tools for learning-- a boundary that 
needs to be blurred ever more.

As a simple example, consider how many students pick up the practice of 
writing software by joining an open-source community of practice like 
Linux and Apache. There may be small groups on a campus, but generally 
such communities of practice are highly distributed. Joining one of them 
entails first becoming a legitimate peripheral participant who works on a 
small project and improves or extends some piece of code-- slowly building 
up a reputation before moving on to more-central tasks and challenges. 
Participants learn new techniques about software practice from watching 
the work of their peers, defending their own work, and participating in 
community discussions about emerging problems. That peer-based learning 
process is about learning to be a practitioner rather than just learning 
about software. Today's students don't want to spend years learning about 
something before they start to learn to be practitioners in that knowledge 
domain.

Of course, such peer-based learning happens to some extent on today's 
campuses in the form of laboratory exercises and studio activities, but 
they are usually labor-intensive for the instructor, requiring much time 
and effort. They are also labor-intensive for the student. But time spent 
on learning is a funny commodity. If the student is passionately engaged 
in acquiring the practice, then time seems to disappear. Passion is the 
key.

Today the Web offers students incredible opportunities to find and join 
niche communities that ignite their passions. That sets the stage, through 
productive inquiry and peer-based learning, for such students to acquire 
both the practice of and knowledge about a field.

In the end, the millions of niche amateur communities-- from the Latin 
word amator, meaning "lover of"-- could provide a powerful learningscape 
for lifelong learning that is grounded in the learning practices that 
students acquire on campuses. That would be a major step toward creating a 
culture of learning for the 21st century.

John Seely Brown is a visiting scholar and adviser to the provost at the 
University of Southern California, as well as independent co-chairman of 
the Deloitte Center for Edge Innovation, a technology-research center in 
California. Previously he was chief scientist of Xerox Corporation and 
director of the Xerox Palo Alto Research Center. This essay is excerpted 
from the foreword to Opening Up Education: The Collective Advancement of 
Education Through Open Technology, Open Content, and Open Knowledge, 
edited by Toru Iiyoshi and M.S. Vijay Kumar, just published by MIT Press. 
Copyright 2008 by MIT Press.