Phil Desenne begins with a brief history of annotation tools at Harvard. There are a lot, for annotating from everything to texts to scrolls to music scores to video. Most of them are collaborative tools. The collaborative tool has gone from Adobe AIR to Harvard iSites, to open source HTML 5. “It’s been a wonderful experience.” It’s been picked up by groups in Mexico, South America and Europe.

Phil works on edX. “We’re beginning to introduce annotation into edX.” It’s being used to encourage close reading. “It’s the beginning of a new way of thinking about teaching and assessing students.” Students tag the text, which “is the beginning of a semantic tagging system…Eventually we want to create a semantic ontology.”

What are the implications for the “MOOC Generation”? MOOC students are out finding information anywhere they can. They stick within a single learning management system (LMS). LMS’s usually have commentary tools “but none of them talk with one another . Even within the same LMS you don’t have cross-referencing of the content.” We should have an interoperable layer that rides on top of the LMS’s.

Within edX, there are discussions within classes, courses, tutorials, etc. These should be aggregated so that the conversations can reach across the entire space, and, of course, outside of it. edX is now working on annotation systems that will do this. E.g., imagine being able to discuss a particular image or fragments of videos, and being able to insert images into streams of commentary. Plus analytics of these interations. Heatmaps of activity. And a student should be able to aggregate all her notes, journal-like, so they can be exported, saved, and commented on, “We’re talking about a persistent annotation layer with API access.” “We want to go there.”

For this we need stable repositories. They’ll use URNs.

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Cliff Lynch is giving talk this morning to the extended Harvard Library community on information stewardship. Cliff leads the Coalition for Networked Information, a project of the Association of Research Libraries and Educause, that is “concerned with the intelligent uses of information technology and networked information to enhance scholarship and intellectual life.” Cliff is helping the Harvard Library with the formulation of a set of information stewardship principles. Originally he was working with IT and the Harvard Library on principles, services, and initial projects related to digital information management. Given that his draft set of principles are broader than digital asset management, Cliff has been asked to address the larger community (says Mary Lee Kennedy).

Cliff begins by saying that the principles he’s drafted are for discussion; how they apply to any particular institution is always a policy issue, with resource implications, that needs to be discussed. He says he’ll walk us through these principles, beginning with some concepts that underpin them.

When it comes to information stewardship, “university community” should include grad students whose research materials the university supports and maintains. Undergrads, too, to some extent. The presence of a medical school here also extends and smudges the boundaries.

Cliff then raises the policy question of the relation of the alumni to the university. There are practical reasons to keep the alumni involved, but particularly for grads of the professional schools, access to materials can be crucial.

He says he uses “scholarly record” for human-created things that convey scholarly ideas across time and space: books, journals, audio, web sites, etc. “This is getting more complicated and more diverse as time goes on.” E.g., author’s software can be part of that record. And there is a growing set of data, experimental records, etc., that are becoming part of the scholarly record.

Research libraries need to be concerned about things that support scholarship but are not usually considered part of the historical record. E.g., newspapers, popular novels, movies. These give insight into the scholarly work. There are also datasets that are part of the evidentiary record, e.g., data about the Earth gathered from sensors. “It’s so hard to figure out when enough is enough.” But as more of it goes digital, it requires new strategies for acquisition, curation and access. “What are the analogs of historical newspapers for the 21st century?” he asks. They are likely to be databases from corporations that may merge and die and that have “variable and often haphazard policies about how they maintain those databases.” We need to be thinking about how to ensure that data’s continued availability.

Provision of access: Part of that is being able to discover things. This shouldn’t require knowing which Harvard-specific access mechanism to come to. “We need to take a broad view of access” so that things can be found through the “key discovery mechanisms of the day,” beyond the institution’s. (He namechecks the Digital Public Library of America.)

And access isn’t just for “the relatively low-bandwidth human reader.” [API’s, platforms and linked data, etc., I assume.]

Maintaining a record of the scholarly work that the community does is a core mission of the university. So, he says, in his report he’s used the vocabulary of obligation; that is for discussion.

The 5 principles

1. The scholarly output of the community should be captured, preserved, organized, and made accessible. This should include the evidence that underlies that output. E.g., the experimental data that underlies a paper should be preserved. This takes us beyond digital data to things like specimens and cell lines, and requires including museums and other partners. (Congress is beginning to delve into this, Cliff notes, especially with regard to preserving the evidence that enables experiments to be replicated.)

The university is not alone in addressing these needs.

2. A university has the obligation to provide its community with the best possible access to the overall scholarly record. This is something to be done in partnership with research libraries aaround the world. But Harvard has a “leadership role to play.”

Here we need to think about providing alumni with continued access to the scholarly record. We train students and then send them out into the world and cut off their access. “In many cases, they’re just out of luck. There seems to be something really wrong there.”

Beyond the scholarly record, there are issues about providing access to the cultural record and sources. No institution alone can do this. “There’s a rich set of partnerships” to be formed. It used to be easier to get that cultural record by buying it from book jobbers, DVD suppliers, etc. Now it’s data with differing license terms and subscription limitations. A lot out of it’s out on the public Web. “We’re all hoping that the Internet Archive will do a good job,” but most of our institutions of higher learning aren’t contributing to that effort. Some research libraries are creating interesting partnerships with faculty, collecting particular parts of the Web in support of particular research interests. “Those are signposts toward a future where the engagement to collect and preserve the cultural records scholar need is going to get much more complex” and require much more positive outreach by libraries, and much more discussion with the community (and the faculty in particular) about which elements are going to be important to preserve.

“Absolutely the desirable thing is share these collections broadly,” as broadly as possible.

3. “The time has come to recognize that good stewardship means creating digital records of physical objects” in order to preserve them and make them accessible. They should be stored away from the physical objects.

4. A lot goes on here in addition to faculty research. People come through putting on performances, talks, colloquia. “You need a strategy to preserve these and get them out there.”

“The stakes are getting much higher” when it comes to archives. The materials are not just papers and graphs. They include old computers and storage materials, “a microcosm of all of the horrible consumer recording technology of the 20th century,” e.g., 8mm film, Sony Betamax, etc.

We also need to think about what to archive of the classroom. We don’t have to capture every calculus discussion section, but you want to get enough to give a sense of what went on in the courses. The documentation of teaching and learning is undergoing a tremendous change. The new classroom tech and MOOCs are creating lots of data, much of it personally identifiable. “Most institutions have little or no policies around who gets to see it, how long they keep it, what sort of informed consent they need from students.” It’s important data and very sensitive data. Policy and stewardship discussions are need. There are also record management issues.

5. We know that scholarly communication is…being transformed (not as fast as some of us would like â?? online scientific journals often look like paper versions) by the affordances of digital technology. “Create an ongoing partnership with the community and with other institutions to extend and broaden the way scholarly communication happens. The institutional role is terribly important in this. We need to find the balances between innovation and sustainability.

Q&A

Q: Providing alumni with remote access is expensive. Harvard has about 100,000 living alumni, which includes people who spent one semester here. What sort of obligation does a university have to someone who, for example, spent a single semester here?

A: It’s something to be worked out. You can define alumnus as someone who has gotten a degree. You may ask for a co-payment. At some institutions, active members of the alumni association get some level of access. Also, grads of different schools may get access to different materials. Also, the most expensive items are typically those for which there are a commercial market. For example, professional grade resources for the financial industry probably won’t allow licensing to alumni because it would cannibalize their market. On the other hand, it’s probably not expensive to make JSTOR available to alumni.

Q: [robert darnton] Very helpful. We’re working on all 5 principles at Harvard. But there is a fundamental problem: we have to advance simultaneously on the digital and analog fronts. More printed books are published each year, and the output of the digital increases even faster. The pressures on our budget are enormous. What do you recommend as a strategy? And do you think Harvard has a special responsibility since our library is so much bigger, except for the Library of Congress? Smaller lilbraries can rely on Hathi etc. to acquire works.

A: “Those are really tough questions.” [audience laughs] It’s a large task but a finite one. Calculating how much money would take an institution how far “is a really good opportunity for fund raising.” Put in place measures that talk about the percentage of the collection that’s available, rather than a raw number of images. But, we are in a bad situation: continuing growth of traditional media (e.g., books), enormous expansion of digital resources. “My sense is…that for Harvard to be able to navigate this, it’s going to have to get more interdependent with other research libraries.” It’s ironic, because Harvard has been willing to shoulder enormous responsibility, and so has become a resource for other libraries. “It’s made life easier for a lot of the other research libraries” because they know Harvard will cover around the margins. “I’m afraid you may have to do that a little more for your scholars, and we are going to see more interdependence in the system. It’s unavoidable given the scope of the challenge.” “You need to be able to demonstrate that by becoming more interdependent, you’re getting more back than you’re giving up.” It’s a hard core problem, and “the institutional traditions make the challenge here unique.”

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Diana Kimball [twitter:dianakimball] is giving a Berkman lunchtime talk on coding as a liberal art. She’s a Berkman Fellow and at the Harvard Business School. (Here are some of her posts on this topic.)

She says that she’s loved computers since she was a kid. But when she went to Harvard as an undergrad she decided to study history, in part because there’s a natural specialization that happens in college: the students who come in as coders are fantastic at coding, whereas Diana had greater strengths as a writer of prose. She found HTML and programming intimidating. But in her third year, she got interested in coding and Internet culture. She was one of the founders of ROFLcon [yay!]. She got hired by Microsoft after college, as a technical product manager with the Powerpoint team in Silicon Valley. “This was culture shock in the best possible way.”

When she graduated in 2009, she and some friends started found the SnarkMarket blog that considers what the new liberal arts might be (inspired by Kottke). She wrote an essay that’s a proposal for coding and decoding. She reads it. (It’s short.) An excerpt:

Coding and Decoding is about all modes of communication, and all are in its view. But it is built with particular attention to the future, and what that future will be like. Technological experts can seem like magicians, conjuring effects wordlessly. By approaching that magic as a collection of component parts instead of an indivisible miracle, we can learn to see through these sleights of typing hands. In seeing through, we will learn to perform them ourselves; and think, as magicians, about the worlds we will build.

Language, now, is about more than communication. It is the architecture behind much of what we experience. Understanding that architecture will allow us to experience more.

Her boyfriend taught her how to code. They spent a lot of time on it. “He picked up on something I’d said and took it seriously.” After two years at Microsoft, she was enthusiastic, but still a beginner. It wasn’t until she started at Harvard Business School that coding really took off for her. The entrepreneurial atmosphere encouraged her to just do it. Plus, she was more of a geek than most of the other students. “This was great for my identity, and for my confidence.” She also found it a social refuge. “It takes a lot of time to get over the hump.” She refers to Ellen Ullman’s “Close to the Machine” that talks about the utility of being arrogant enough to obsess over a project, cycling back to humility.

She decided to code up her own site for a project for school, even though the team had been given the money to hire devs for the task. Last fall she took the famous CS50 course [Harry Lewis, who created the course in about 1981, is sitting next to me.] CS50 teaches C, targeted at people who are either taking only that one class, or are going to take many more. For her final project, she did a project that used multiple APIs that she was very proud of. She’s also proud of her Ruby projects folder. Each project is something she was trying to teach herself. She’s more proud of the list than the finished products.

“Learning to code means reclaiming patience and persistence and making them your stubborn own.” [nice]

Ideally, everyone should be exposed to programming, starting at 5 yrs old, or even earlier, Diana says. Seymore Papert’s “Mind-Storms” has greatly influenced her thinking about how coding fits into education and citizenship. At a university, it ought to be taken as a liberal art. She quotes Wikipedia’s definition. And if “grammar, rhetoric, and logic were the core of the liberal arts,” then that’s sound like coding. [Hmm.] What the law was to the liberal arts, programming ought to be, i.e., that which you try if you don’t know what else to do with your liberal arts degree.

Why isn’t it seen that way? When computer scientists teach you, they teach they way they learned: at school. But many of the best programmers are self-taught. CS50 does give a variety of assignments, but it’d be better if students solved their own problems much earlier.

But the number one problem is the academic attitude, she says. Students get fixated on the grade, even when it doesn’t matter. Coding is critical for children because debugging is part of it, as Papert says. But grades are based on the endpoints. Coding is much more like life: You’re never done, you can always make it better.

Diana has a proposal. Suppose coding classes were taught like creative writing workshops. Take it whenever you’re ready. Taught by hackers, esepcially autodidacts. It’d vary in substance — algorithms, apis, etc. — and you’d get to choose. You’d get to see something on screen that you’d never seen before And you’d be evaluated on ingenuity and persistence, rather than only on how well your code runs.

She says what her syllabus would look like:

• Robin Sloan’s novel “Mr. Penumbra’s 24-Hour Bookstore.”

• Critical study of selected Github pull requests — how open source projects work, how to rise in the community

• Bring in an API evangelist from an interesting company, maybe bring in two and let

• Neal Stephenson’s “In the Beginning Was the Command Line“

“Coding should be taught in the same breath as expository writing… Everyone deserves to be exposed to it.” She’s not sure if it should be required.

She quotes Papert: “…the most powerful idea of all is the idea of powerful ideas.” There’s no better example of this, she says, than open source software. And David Foster Wallace’s commencement address: “Learning how to think really means learning to exercise some control over how and what you think…If you cannot exercise this sort of choice in adult life, you will be totally hosed.” Diana says that’s her. She was wrapped up in writing from an early age. She has a running internal commentary. [Join the club!] Coding swaps in a different monologue, one in which she’s inventing thing. That’s the greatest gift: her internal monologue is much more useful and interesting. “If you wanted to be a novelist in 1900, you’d want to be a programmer today.” The experience of creating something that people use is so motivating.

Q&A

Q: Would you be willing to webcast yourself programming and let people join in? I do this all the time when at hackathons. I think, OMG, there must be 10,000 kids in India who want to be here. And so here they are. “Hackers at Berkeley” does this really well.

A: That’s awesome. I want more people to have more access to that experience of sharing.

Q: Are you familiar with RailsBridge — non-computer scientists who are teaching themselves how to code via weekend workshops.

A: RailsBridge is extraordinary. It’s great to see this happening outside of the university context.

A: [me] Great talk, and I’m a humanities major who spends most of his hobby time programming. But aren’t you recommending the thing that you happen to love? And programming as opposed to traditional logic is an arbitrary set of rules…

Q: Yes, but it would be really useful if more people loved it. We could frame it in a way that is exciting for humanities majors. I’m proposing an idea rather than making an airtight argument. “You’re basically right but I don’t really care” (she says laughing :).

Q: I like your idea of teaching it like a writers workshop so that it doesn’t turn into just another course. But I’m not sure that colleges are the best at doing that.

A: not everyone loves programming.

Q: [harry lewis] I take responsibility for eliminating the Harvard requirement for a programming course. Also, take a look at code.org. Third, the academic world treats computer science the way it does because of our disciplinary specialization. That label — computer science — came about in the context of fields like political science, and arose when computers were used not for posting web sites but for putting people on the Moon where a bug could kill someone. The fact that CompSci exists in academic departments will make it very difficult for your vision of computing to exist, just as creative writing is often an uneasy fit into English curricula.

A: That’s very fair. I know it’d be hard. RIT has separate depts for CompSci and coding.

Q: There’s an emergent exploration of coding in Arts schools, with a much more nimble, plug and play approach, very similar to the one you describe. My question: What do the liberal arts have to offer coding? Much of coding is quite new, e.g., open source. These could be understood within a historical context. Maybe these need to be nurtured, explored, broken. Does seeing coding as a liberal art have something to offer sw development?

A: ITP is maybe the best example of artists working with coders. Liberal Arts can teach programmers so much!

Q: Can we celebrate failure? That’d be a crucial part of any coding workshop.

A: Yes! Maybe “find the most interesting bug” and reward introspection about where you’ve gone wrong. But it’s hard in a class like CS50 where you’re evaluating results.

Q: This is known as egoless programming. It’s 40 years old, from Weinberger [no relation].

Q: You’re making a deeper point, which is not just about coding. The important thing is not the knowledge you get, but the way you get there. Being self-reflective about you came about how you learn. You can do this with code but with anything.

A: You’re so right. Introspection about the meta-level of learning is not naturally part of a course. But Ruby is an introspective language: you can ask any object what it is, and it will tell you. This is a great mirror for trying to know yourself better.

Q: What would you pick to teach?

A: I love Ruby. It would be a good choice because there’s a supportive community so students can learn on their own afterwards, and it’s an introspective language. And the lack of ornament in Ruby (no curly braces and little punctuation) makes it much more like English. The logic is much more visible. (My preference is Sinatra, not Rails.)

Q: What sort of time commitment the average person would have to put in to have a basic grasp of a programming language? Adults vs. children learning it?

A: I’d love to see research on this. [Audience: Rottmeyers, CMU (?)] A friend of mine reported he spent 20 hours. The learning curve is very halting at first. It’s hard to teach yourself. It helps to have a supportive in-person environment. CS50 is a 10-20 hour commitment/week and who has that sort of time except for fulltime students? To teach yourself, start out a few hours a time.

Q: How about where the MOOCs are going? Can you do a massively online course in compSci that would capture some of what you’re talking about?

A: The field is so focused on efficiency that MOOCs seem like an obvious idea. I think that a small workshop is the right way to start. CS50 requires so much fear of failure and resilience that it wouldn’t have been a good way for me to start. At CS50, you can’t let others read your code.

Q: We shouldn’t put together Computer Science and programming. Programming is just a layer of expression on top of computer science. You don’t need compSci to become a programmer. And the Net is the new computer; we’re gluing together services from across the Net. That will change how people think about programming because eveyrone will be able to do it. The first language everyone should learn is ifttt.com

Q: I’m a NY Times journalist. I love languages. And I love the analogy you draw. I’m 30. Do you think coding is really essential? Would it open my eyes as a journalist?

A: It’s never too late. If you keep asking the question, you should probably do it. You don’t have to be good at it to get a lot out of it. It’s so cool that your children are learning multiple languages including coding. Learn alongside them.

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Siva Vaidhyanathan [twitter: sivavaid] has a really well-done (as usual) article that reminds us that for all the excitement about Massive Open Online Courses — which he shares — we still have to figure out how to do them right. There are lots of ways to go wrong. (And I should hear note that I’m posting this in order to: (1) recommend Siva’s article, and (2) make an obvious point about MOOCs. Feel free to stop here.)

The fundamental issue, of course, is that real-world ed doesn’t scale very well. The largest classes in the real world are in the hundreds (oh, maybe some school has a course with thousands), and those classes are generally not held up as paradigms of Western ed. Further, traditional ed doesn’t scale in the sense that not everyone gets to go to college.

So, now we have a means for letting classes get very big indeed. Hundreds of thousands. Put in the terms of Too Big to Know, the question is: how do you make that enormous digital classroom smarter than the individuals in it? 2B2K’s answer (such as it is) is that you make a room smart by enabling its inhabitants to create a knowledge network.

• Such a network would at a minimum connect all the participants laterally, as well as involving the teacher
• It would encourage discussion of course topics, but be pleased about discussions that go off topic and engage students socially.
• It would enable the natural experts and leaders among the students to emerge.
• It would encourage links within and outside of the course network.
• This network would enable students to do their work online and together, and make those processes and their traces fully available to the public.
• All the linking, discussions, answered questions, etc., would be fed back into the system, making it available to everyone. (This assumes there are interactions that produce metadata about which contributions are particularly useful.)
• It would encourage (via software, norms, and evaluations) useful disagreements and differences. It doesn’t always try to get everyone onto exactly the same page. Among other things, this means tolerating — appreciating and linking to — local differences among the students.
• It would build upon the success of existing social tools, such as liking, thumbs upping, following…
• Students would be encouraged to collaborate, rather than being evaluated only as individual participants.
• The learning process would result in a site that has continuing value to the next students taking the course and to the world.

I’m not trying to present a Formula for Success, because I have no idea what will actually work or how to implement any ideas. Fortunately, there are tons of really smart people working on this now, with a genuine spirit of innovation. All I’m really saying is something obvious: to enable education to scale so that MOOCs don’t become what no one wants them to be — cyber lecture halls — it’s useful to think about the “classroom” as a network.

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My latest column in KMWorld is about why your business needs scholars. In fact, though, it’s about why the idea of scholarship is more helpful than focusing your thinking on knowledge.

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If you want to read a brilliant application of some of the ideas in Too Big to Know to our educational system, read A New Culture of Learning by Douglas Thomas and John Seely Brown. And by “application of” I mean “It was written a year before my book came out and I feel like a dolt for not having known about it.”

DT and JSB are thinking about knowledge pretty much exactly the way 2b2k does. What they call a “collective,” I call a “knowledge network.” With more than a hat tip to Michael Polanyi, they talk insightfully about “collective indwelling,” which is the depth of insight and topical competency that comes from a group iterating on ideas over time.

Among other things, they write provocatively about the use of games and play in education, not as a way to trick kids into eating their broccoli, but as coherent social worlds in which students learn how to imagine together, set goals, gather and synthesize information, collectively try solutions, and deepen their tacit knowledge. DT and JSB do not, however, so fetishize games that they lose site of the elements of education a game like World of Warcraft (their lead example) does not provide, especially the curiosity about the world outside of the game. On the contrary, they look to games for what they call the “questing disposition,” which will lead students beyond problem-solving to innovation. Adding to Johan Huizinga‘s idea that play precedes culture, they say that games can help fuse the information network (open and expansive) with the key element of a “bounded environment of experimentation” (116). This, they say, leads to a new “culture of learning” (117). Games are for them an important example of that more important point.

It’s a terrific, insightful, provocative book that begins with a founding assumption that it’s not just education that’s changing, but what it means to know a world that is ever-changing and now deeply connected.

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Eric Schmidt is being interviewed by Jeff Goldberg about the Net and Democracy. I’ll do some intermittent, incomplete liveblogging…

NOTE: Posted without having even been re-read. Note note (a few hours later): I’ve done some basic cleanup.

After some amusing banter, Jeff asks Eric about how responsible he felt Google was for Arab Spring. Jeff in passing uses the phrase “Internet revolution.”

ES: Arab Spring was enabled by a failure to censure the Internet. Google enabled people to organize themselves. Especially in Libya, five different militias were able to organize their armed revolt by using the Net. It’s unfair to the people who died to call it an “Internet revolution.” But there were fewer people who died, in part because of the incessant media coverage. And we’ve seen that it’s very easy to start what some call an Internet revolution, but very hard to finish it.

JG: These were leaderless revolutions, crowdsourced revolution. But in Egypt the crowd’s leaders were easily pushed aside after Mubarek fell.

ES: True leaders are very hard to find. In Libya, there are 80 militias, armed to the teeth. In most of the countries there were repressed Muslim groups that have emerged as leaders because they organized while repressed. Whoever takes over inherits financial and social problems, and will be thrown out if they fail.

JG: Talk about Google’s tumultuous relationship with China…

ES: There are lots of reasons to think that China works because its citizens like its hierarchical structure. But I think you can’t build a knowledge society without freedom. China wants to be a knowledge society. It’s unclear if China’s current model gets them past a middle income GDP. Google thought that if we gave them free access to info, the Chinese people would revolt. We were wrong, and we moved Google to Hong Kong, on the open side of the Great Firewall. (We had to because that’s the Chinese law.) Now when you enter a forbidden query, we tell the user that it’s likely to be blocked. We are forbidden from announcing what the forbidden terms are because we don’t want employees put in jail.

JG: Could Arab Spring happen in China? Could students organize Tianamen Square now?

ES: They could use the Chinese equivalent of Twitter. But if someone organizes a protest, two people show up, plus 30 media, and 50 police.

JG: Google’s always argued that democratization of info erodes authoritarian control. Do you still believe that?

ES: The biggest thing I’ve learned is how hard it is to learn about the differences among people in and within countries. I continue to believe that this device [mobile phone] will change the world. The way to solve most of the world’s problems is by educating people. Because these devices will become ubiquitous, it’ll be possible to see how far we humans can get. With access to the Net, you can sue for justice. In the worst case you can actually shame people.

JG: And these devices can be used to track people.

ES: Get people to understand they have choices, and they will eventually organize. Mobiles tend to record info just by their nature. The phone company knows where you are right now. You’re not worried about that because a law says the phone company can’t come harass you where you’re sitting. In a culture where there isn’t agreement about basic rights…

JG: Is there evidence that our democracy is better off for having the Internet?

ES: When we built the Net, that wasn’t the problem we were solving. But more speech is better. There’s a lack of deliberative time in our political process. Our leaders will learn that they’ll make better decisions if they take a week to think about things. Things will get bad enough that eventually reason will prevail. We complain about our democracy, but we’re doing quite well. The US is the beacon of innovation, not just in tech, but in energy. “In God we trust … all others have to bring data.” Politicians should just start with some facts.

JG: It’s easier to be crazy and wrong on the Net.

ES: 0.5% of Americans are literally crazy. Two years ago, their moms got them broadband connections. And they have a lot of free time. Google is going to learn how to rank them. Google should enable us to hear all these voices, including the crazy people, and if we’re not doing that, we’re not doing our job.

JG: I googled “Syria massacre” this morning, and the first story was from Russia Today that spun it…

ES: It’s good that you have a choice. We have to educate ourselves and our children. Not everything written is true, and very powerful forces want to convince you of lies. The Net allows that, and we rank against it, but you have to do your own investigation.

JG: Google is hitting PR problems. Talk about privacy…

ES: There’s no delete button on the Net. When you’re a baby, no one knows anything about you. As you move through life, inevitably more people know more about you. We’re going to have to learn about that. The wifi info gathering by StreetView was an error, a mistake, and we’ve apologized for it.

JG: The future of journalism?

ES: A number of institutions are figuring out workable models. The Atlantic [our host]. Politico. HuffingtonPost. Clever entrepreneurs are figuring out how to make money. The traditional incumbents have been reduced in scale, but there are plenty of new voices. BTW, we just announced a tablet with interactive, dynamic magazines. To really worry about: We grew up with the bargain that newspapers had enough cash flow to fund long term investigative research. That’s a loss to democracy. The problem hasn’t been fully solved. Google has debated how to solve it, but we don’t want to cross the content line because then we’d be accused of bias in our rankings.

JG: Will search engines search for accuracy rather than popularity?

ES: Google’s algorithms are not about popularity. They’re about link structures, and we start from well-known sources. So we’re already there. We just have to get better.

JG: In 5 yrs what will the tech landscape look like?

ES: Moore’s Law says that in 5 yrs there will be more power for less money. We forget how much better our hw is now than even 5 years. And it’s faster than Moore’s Law for disks and fiber optic connections. Google is doing a testbed optical installation. At that bandwidth all media are just bits. We anticipate a lot of specialty devices.

JG: How do you expect an ordinary, competent politician to manage the info flow? Are we inventing tech that is past our ability to process info?

ES: The evidence is that the tech is bringing more human contact. The tech lets us express our humanity. We need a way of sorting politicians better. I’d suggest looking for leaders who work from facts.

JG: Why are you supporting Obama?

ES: I like having a smart president.

JG: Is Romney not smart?

ES: I know him. He’s a good man. I like Obama’s policies better.

Q&A

Q: Our connectivity is 3rd world. Why haven’t we been able to upgrade?

A: The wireless networks are running out of bandwidth. The prediction is they’ll be saturated in 2016. Maybe 2017. That’s understandable: Before, we were just typing online and now we’re watching movies. The White House in a few weeks is releasing a report that says that we can share bandwidth to get almost infinite bandwidth. Rather than allocating a whole chunk that leaves most of it unused, using interference databases we think we can fix this problem. [I think but please correct me: A database of frequency usages so that unused frequencies in particular geographic areas can be used for new signals.]

A: The digital can enhance our physical connections. E.g., a grandmother skyping with a grandchild.

JG: You said you can use the Net to shame govts. But there are plenty of videos of Syria doing horrible things, but it’s done no good.

ES: There are always particularly evil people. Syria is the exception. Most countries, even autocratic ones, are susceptible to public embarrassment.

Q: Saying “phones by their nature collect data” evades responsibility.

ES: I meant that in order to their work, they collect info. What we allow to be done with that info is a legal, cultural issue.

Q: Are we inherently critical thinkers? If not, putting info out there may not lead to good decisions.

ES: There’s evidence that we’re born to react quickly. Our brains can be taught reasoning. But it requires strong family and education.

Q: Should there be a bill of rights to simplify the legalese that express your privacy rules?

ES: It’s a fight between your reasonable point of view, and the lawyers and govt that regulate us. Let me reassure you: If you follow the goal of Google to have you as a customer, the quickest way to lose you is to misuse your information. We are one click away from competitors who are well run and smart. [unless there was money in it, or unless they could get away with it, or…]

Q: Could we get rid of representative democracy?

ES: It’ll become even more important to have democratic processes because it’s all getting more complicated. For direct democracy we’d have to spend all day learning about the issues and couldn’t do our jobs.

JG: David Brooks, could you comment? Eric is an enormous optimist…

ES: …The evidence is on my side!

JG: David, are you as sanguine that our politicians will learn to slow their thinking down, and that Americans have the skills to discern the crap from the true.

David Brooks: It’s not Google’s job to discern what’s true. There are aggregators to do this, including the NYT and TheBrowser. I think there’s been a flight to quality. I’m less sanguine about attention span. I’m less sanguine about confirmation bias, which the Web makes easier.

ES: I generally agree with that. There’s evidence that we tend to believe the first thing we hear, and we judge plus and minus against that. The answer is always for me culture, education.

Q: Will there be a breakthrough in education?

ES: Education changes much more slowly than the world does. Sometimes it seems to me that education is run for the benefit of the teachers. They should do measurable outcomes, A-B testing. There’s evidence that physics can be taught better by setting a problem and then do a collaborative effort, then another problem…

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Google has posted my authors@google talk. Thank you, Google!

And Steve Hargadon has posted the hour interview he did last night as part of his Future of Education series, in which we talked about knowledge and education. Thank you, Steve Hargadon!

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Skip Walter’s post about his growing acceptance and understanding of the need for digital humanities hits on so many of my intellectual pleasure spots, starting with Russ Ackoff’s knowledge network, and including Kate Hayles and Cathy Davidson, and more and more. (Yes, he mentions “Too Big to Know” in passing, but that’s irrelevant to my reaction.)

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Alison Head, who is at the Berkman Center and the Library Information Lab this year, but who is normally based at U of Washington’s Info School, is giving a talk called “Modeling the Information-Seeking Process of College Students.” (I did a podcast interview with her a couple of months ago.)

Project Information Literacy is a research project that reaches across institutions. They’ve (Michael Eisenberg co-leads the project) surveyed 11,000 students on 41 US campuses to find out how do students find and use information. They use voluntary samples, not random samples. But, Alison says, the project doesn’t claim to be able to generalize to all students; they look at the relationships among different kinds of schools and overall trends. They make special efforts to include community colleges, which are often under-represented in studies of colleges.

The project wanted to know what’s going through students’ heads as they do research. What’s it like to be a student in the digital age? “How do students define the research process, how do they conceptualize it” throughout everyday school life, including non-course-related research (e.g., what to buy).

Four takeaways from all five studies:

1. “Students say research is more difficult for them than ever before.” This is true both for course-related and everyday life research. Teachers and librarians denied this finding when it came out. But students describe the process using terms of stress (fear,angst, tired, etc.) Everyday-life research also had a lot of risk associated with it, e.g., when researching medical problems.

Their research led the project to come up with a preliminary model based on what students told them about the difficulties of doing research that says in the beginning part of research, students try to define four contexts: big picture, info-gathering, language, situational. These provide meaning and interpretation.

a. Big picture. In a focus group, a student said s/he went to international relations class and there was an assignment on how Socrates would be relevant to a problem today. Alison looked at the syllabus and wondered, “Was this covered?” Getting the big picture enables students to get their arms around a topic.

b. Info gathering. “We give students access to 80 databases at our small library, and they really want access to one,” says Barbara Fister at Gustavus Adolphus.

c. Language. This is why most students go to librarians. They need the vocabulary.

d. Situational. The expectations: how long should the paper be, how do I get an A, etc.? In everyday life, the situational question might be: how far do I go with an answer? When do I know enough?

Students surveyed said that for course related research they almost always need the big picture, often need info-gathering, sometimes need language, and sometimes need situational. Students were 1.5x more likely to go to a librarian for language context. For everyday-life, big picture is often a need, and the others are needed only sometimes. Many students find everyday-life research is harder because it’s open-ended, harder to know when you’re done, and harder to know when you’re right. Course-related research ends with a grade.

2. “Students turn to the same ‘tried and true’ resources over and over again.”. In course research, course readings were used 97% of the time. Search engines: 96%. Library databases: 94%. Instructors: 88%. Wikipedia: 85%. (Those are the 2010 results. In 2009, everything rose except course readings.) Students are not using a lot of on-campus sources. Alison says that during 20 years of teaching, she found students were very disturbed if she critiqued the course readings. Students go to course readings not only to get situational context, but also to get big picture context, i.e., the lay of the land. They don’t want you critiquing those readings, because you’re disrupting their big picture context. Librarians were near the bottom, in line with other research findings. But “instructors are a go-to source.” Also, note that students don’t go online for all their info. They talk to friends, instructors, etc.

In everyday life research, the list in order is: Search engines 95%, Wikipedia 84%, friends and family 87%, personal collection 75%, and government sites 65%.

Students tend to repeat the same processes.

3. “Students use a strategy of predictability and efficiency.” They’re not floundering. They have a strategy. You may not like it, but they have one. It’s a way to fill in the context.

Alison presents a composite student named Jessica. (i) She has no shortage of ideas for research. But she needs the language to talk about the project, and to get good results from searching. (ii) Students are often excited about the course research project, but they worry that they’ll pick a topic “that fails them,” i.e., that doesn’t let them fulfill the requirements. (iii) They are often risk-averse. They’ll use the same resource over and over, even Project Muse for a science course. (“I did a paper on the metaphor of breast cancer,” said one student.) (iv) They are often self-taught and independent, and try to port over what they learned in high school. But HS works for HS, and not for college. (iv) Currency matters.

What’s the most difficult step? 1. Getting started 84%. 2. Defining a topic 66%. Narrowing a topic 62%. Sorting through irrelevant results 61%. Task definition is the most difficult part of research. For life research, the hardest part is figuring out when you’re done.

So, where do they go when they’re having difficulty in course research? They go to instructors, but handouts fall short: few handouts the project looked at discussed what research means (16%). Six in ten handouts sent students to the library for a book. Only 18% mention plagiarism, and few of those explained what it is. Students want email access to the instructor. Second, most want a handout that they can take with them and check off as they do their work. Few hand-outs tell students how to gather information. Faculty express surprise at this, saying that they assume students know how to do research already, or that it’s not the prof’s job to teach them that. They tend not to mention librarians or databases.

Students use ibrary databases (84%), OPAC (78%), study areas (72%), check library shelves (55%), cafe (48%). Only 12% use the online “Ask a librarian” reference. 20% consult librarians about assignments, but 24% ask librarians about the library system.

Librarians use a model of scholarly thoroughness, while students use a model of efficiency. Students tend to read the course materials and then google for the rest.

Alison plays a video:

How have things changed? 1. Students contend with a staggering amount of information. 2. They are always on and always being notified. 3. It’s a Web 2.0 sharing culture. The old days of dreading group projects are ending; satudents sometimes post their topics on Facebook to elicit reactions and help. 4. The expectations from information has changed.

“Books, do I use them? Not really, they are antiquated interaces. You have to look in an index, way in the back, and it’s not hyperlinke.”

[I moderated the Q&A so I couldn’t liveblog it.]
TAGS: -berkman

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