About Content

4 Oct

I was invited to participate in the Olin Innovation Lab #3 on the “Content” panel, which starts in about 3 hours. It forced me to reflect! I share with you the result: random thoughts on “Content” and Higher Ed.

The Accessible Tier.

I predict the continued growth and importance of the “accessible tier” of academic content: individuals feeling comfortable sharing products of thought that haven’t been officially vetted & blessed.  Things like white papers in open repositories. Even blogs, God forbid.

Student Scholarship.

Students will increasingly produce scholarship. That is–share thinking with the world, via new media–as part of their learning. And this scholarship will be influential and fuel the previous bullet. (Students will show their faculty how to produce new kinds of scholarship).

What is the New Book?

We’re waiting for Godot–yes, the electronic version of the scholarly monograph. It may never come. It might be like Robert Darnton’s beautiful socially-networked, layered thought pyramid: a popular book underscored by a series of white papers and then the digitized primary sources, all wrapped in a socially-aware container that invites anyone to interact. Readers can rewrite the pieces into their own scholarship that becomes part of the pyramid. An aggregating structure half thought, half conversation, half research data, half publication. Or the new form of monograph might go the opposite way: be rather an element than a molecule: we may register thought “nuggets” that anyone can then recombine into their own sequences. Who knows!

Revival of Learning.

Changes in content fuel a revival of pedagogy and research methodology. Because if you find yourself teaching and researching in new forms, you have to ask “how do I do this?” And this helpful reflection leads you to core principles always worth re-articulating. (This is why Blended Learning and Distance Learning have, perhaps counter-intuitively, helped contribute to a culture of thinking about learning that influences traditional classroom learning).

Revival of Community.

Universities will look for core communities to guide them.  Non-sectarian groups of people–faculty, students, staff, alumni, visitors–who will form to help the institution fluidly move through an era of changing forms of content, and changing ways of teaching and researching. “Should we do this new thing?” they’ll ask, then they’ll look to see if it helps in the classroom. In the research lab. In the thought crucible where you review and synthesize the world of scholarship. Their guiding star will be a shared understanding of what leads to good learning.

Challenges of Library & IT Organizations: Politics v. Innovation

Library & IT’s challenges are politics and innovation.  They have the one and they need both. Libraries and IT departments are lean, efficient organizations designed to support what exists well–current forms of content, teaching, scholarship, etc. Not necessarily figure out what comes next.  There’s political interest in us continuing to do what we do now (people still want journals and email, for instance). To figure out how to do the next thing, we have to shift resources into entrepreneurial activities. R&D.

What this means is we have to become less competent at what we are doing now (take resources away from it) in order to become incompetent at what we will be doing later in order then to (potentially) become competent at what we will be doing later (because you have to be bad at something before you can be good at it; that’s learning).  In other words, we have to fail twice to have a chance to succeed once. Who wants to fail twice? We also need to keep our jobs, pay the mortgage, etc. Hence our challenge.

The New Metadata.

I’m thinking about this article Gregory Crane wrote, “What Do You Do With a Million Books?” Crane imagines a digital library, not of flat text files available for searching, but of active computer-mitigated entities that read each other.  I just love this idea: the history book that, while we are sleeping, reads the nearby books, say maps, and forges connections for us. When we wake up, we see a new, hybrid product, maybe that represents itself in some new infographic like the beautiful data pictures made famous recently by the New York Times, because that’s the only way it can be represented.

This, it seems to me, is a territory beyond metadata and full-text search. Metadata is limited by the process that makes it. Who picks the terms? Etc. Full text-search is limited by the searcher. What are they looking for? Etc. In theory books that read themselves are less limited. Yes, by the program that tells them how to read, but we’ll use some kind of open-minded A.I. model for that.

Learning Intelligence.

Another very interesting trend for me is the thoughtful computer mitigation of the previous topic, but applied to learning. Call it “Learning Intelligence.” The idea is that large amounts of course communication are happening in machine-readable formats. Even in traditional courses. Word docs. Forum conversations. Emails. Blogs. Twitter posts. If we can gather and reflect on this data, the idea continues, we’ll have a window into learning processes that have heretofore been almost utterly inscrutable (probably only penetrable by the instructor’s intuition). And if we add pattern recognition, linguistic analysis, and data visualization layers, we can give the data back to the teacher in ways that can meaningfully inform and give feedback into and become formative assessment for the course.

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