I have been reading Steven Brill’s new book Class Warfare. After a few chapters it hits you in the face: schools cannot be fixed. Brill describes a variety of wonderful people who have realized how schools are failing kids, thrown themselves at the problem, and failed. This has been going on for decades. Why? Because of unions, bad teachers, poverty, race, wrong theories, not caring about children. Well, no. They fail because it is impossible to put a couple of dozen same-age children in a room all day, and day after day, and thereby produce 24 youngsters who know the same thing at the same time. Think about how just plain silly trying to do that is.

Schools we have now in the United States were created in the 19th and 20th centuries. Back then, building schools gave children a place to go to learn reading, writing, arithmetic, and subjects such as history, science, and languages. Except for rich kids whose parents hired tutors to teach them at home, school was about the only place a child could get this knowledge.

By the time we arrived in the closing decades of the 20th century, schools were dominating the lives of youngsters from late toddling until late teens. [Then, convention demands, on to college for more of the same.] Brill does a great job of describing the true disasters schools have become. He quotes Joel Klein, who attempted reform as New York City schools chancellor, as frequently observing: “You just can’t make this s**t up.” Having coordinated a major Mentor project in the New York City schools (1982-1992), and coached and judged high school debaters in the New York city schools (1993-2009), I can tell you Mr. Klein is correct. Schools are seldom much of a place to go to learn very much reading, writing, arithmetic, and subjects such as history, science, and languages.

But lo, in the 21st century there is another place a student can go to learn those things: the web.

The student can now have the web in his pocket or under her arm on a mobile smart phone or tablet. Every kid who has a mobile browser has access to what is known that is equal to the access of every other kid that has such a device. And the device has no idea how rich its owner is, whether it is a boy or girl, and what the kid’s age, nationality, or race are. The device has no expectation of what the kid can learn and it offers equal knowledge to all.

The primary location of knowledge is now the web — certainly much more than the dribs and drabs in textbooks that weigh down school backpacks. Why the heck are we expecting to teach knowledge to our children by dumbing subjects down and filtering them through places where “You just can’t make this s**t up” — in places called schools, where so many incredibly talented and determined people have failed to make things better?

If we make sure all the kids have their own web access to knowledge, schools can be made to work as places to meet with teachers, do discourse, arts, and sports. They will be community centers and socialization places, and of course babysitters for working parents.

Suggestion: Let’s take a break from throwing gifted people, billions of dollars, and yet another generation of children into schools, expecting somehow the kids will learn, and learn equally. Let’s get back to that after we take these steps:

• See to it every kid has his or her own web browser with wireless access.
• Make sure the kids know how to find knowledge to learn on the web.
• Put some real effort into optimizing online knowledge for search engines and natural vetting.

Every child will not emerge from this new approach with the same cookie cutter education. But each child will experience equal access, opportunity, and expectations from the bountiful new virtual knowledge online commons offered freely to all on the web.

BTW: I recommend Class Warfare, based on Brill’s forthright portrayal of the New York City public schools, Teach for America, and other aspects of the education debacle with which I have personal experience. For one thing, it is hard to read this book and continue to think we can “fix the schools.” The great blessing is that the internet and individual access devices have arrived, giving us a new way to put knowledge that is untethered to schools into the hands of any and every child.

NatureNews reported yesterday that the clock for four-legged creatures has been turned back 18 million years. Anyone connected to the internet can learn this new information from the scientists who made the discovery. The video above is narrated by one of these paleontologists and the report from NatureNews sketches the facts.

As OER (open educational resources) these materials are the footprints of the future. Previous educational resources, especially printed ones like textbooks, are now obsolete on the dating of walking tetrapods. They will continue to place walking tetrapods 18 million years later than they should be on their timelines — for months or years until they can be updated and reprinted.

The NatureNews report and video are Five Star OER because they can be used as a direct interface to students from big science in almost real time. In his narration of the video, Dr. Ahlberg says: “I have been working personally in this field since the mid-1980s. I have had over 20 publications in Nature. And this is the most important paper that I have ever worked on.”

Watch the video and I think you will agree that the learning experience is worth making sure paleontology students see it. I was only #352 to watch it on YouTube. What can educators do to make sure Walking with Tetrapods gets into the learning mainstream? There is a lot we can do by optimizing the video for learning networks and linking to it robustly. Educators can fundamentally upgrade global learning by concentration on Five Star OER, and letting go of analog resources with less learning star power.

↓

↓

↓

↓

↓

The knowledge that our brain takes in as we learn is also a network. The networking of knowledge — study subjects that form what is known by humankind –  is illustrated in the images here from the Los Alamos Map of Science. As we use the internet to learn, we can observe and learn the patterns that emerge from knowledge networking online. The internet is the first mirror medium of the networking of ideas we have ever had. It promises a global golden age of learning. We should be using it more in education and working to stimulate its cognitive networking.

↓

Before the internet mirrored the networking of ideas, the main way students had for locating nodes of stuff to learn by connecting ideas is illustrated here: We would get them one-by-one out of books and then make the network of their relationships in our minds.

↓

↓

↓

Since the internet came along, educators have used content management systems, curricula, and the like to harvest learning stuff nodes from the internet and organize the nodes into patterns to convey to students’ minds. This approach should be understood and developed so as to include in the harvest the naturally networking patterns of the open internet.

Can it be that the grand idea is like a superorganism, as described in a fascinating article in SEED magazine on this topic: “Our bodies harbor 100 trillion bacterial cells, outnumbering our human cells 10 to one. It’s easy to ignore this astonishing fact. Bacteria are tiny in comparison to human cells; they contribute just a few pounds to our weight and remain invisible to us.” The following are some excerpts from the article [with some comments by me] that suggest similarities between the communication among our bacteria and the behavior of knowledge online. The fundamental reason they are alike is that bacteria and bits of learnable knowledge are small pieces that communicate in network patterns.

Indeed, several scientists have begun to refer to the human body as a “superorganism” whose complexity extends far beyond what is encoded in a single genome.

The physiology of a superorganism would likely look very different from traditional human physiology. [Learning resources in libraries look very different from what is online.] There has been a great deal of research into the dynamics of communities among plants, insect colonies, and even in human society. What new insights could we gain by applying some of that knowledge to the workings of communities in our own bodies? [to the workings of knowledge when it gets online] . . . .

Even confined in their designated body parts, microbes exert their effects by churning out chemical signals for our cells to receive. [Yesterday I posted about signaling by cells and signaling by learning nodes.] Jeremy Nicholson, a chemist at Imperial College of London, has become a champion of the idea that the extent of this microbial signaling goes vastly underappreciated. Nicholson had been looking at the metabolites in human blood and urine with the hope of developing personalized drugs when he found that our bodily fluids are filled with metabolites produced by our intestinal bacteria. He now believes that the influence of gut microbes ranges from the ways in which we metabolize drugs and food to the subtle workings of our brain chemistry. [The influence is a form of connectivity.]

Scientists originally expected that the communication between animals and their symbiotic bacteria would form its own molecular language. But McFall-Ngai, an expert on animal-microbe symbiosis, says that she and other scientists have instead found beneficial relationships involving some of the same chemical messages [again: signaling connects] that had been discovered previously in pathogens. Many bacterial products that had been termed “virulence factors” or “toxins” turn out to not be inherently offensive signals; they are just part of the conversation between microbe and host. [Open educational resources (OER) often are, and need to be, able to converse (signal) each other.]

What the e-Commerce world calls SEO (search engine optimization) is one way to give resources signals they can use to reach out to related stuff online. For OER, SEO is vital, but just a first step in the creation of signaling pathways. There are other very effective signal methods inherent in learning resources including: experts linking to (creating a network with) other OER they respect, landing pages that point (signal toward) excellent OER, and RSS-type signals that roll out expertise as it is published.

So would this signaling stuff work in a real network? Yes, and molecular biology is a very compelling model. The Wikipedia article on Cell Signaling (from which the above illustration is taken) explains:

Traditional work in biology has focused on studying individual parts of cell signaling pathways. Systems biology research helps us to understand the underlying structure of cell signaling networks and how changes in these networks may affect the transmission and flow of information. Such networks are complex systems in their organization and may exhibit a number of emergent properties . . . .

The following excerpt is from a current article in Molecular Systems Biology. Click on the small illustration from the article at the right to see a chart of network relationships — which are the real world way in which life itself works. Instead of bundling a course or textbook in a pdf and tossing it online, how can we instead optimize the knowledge within the OER with some of these principles in the excerpt that follows by which our cells keep us alive and keep us thinking?

Despite their value in aggregating diverse and scattered information, protein networks inferred purely from data and those assembled from the literature suffer from significant and complementary weaknesses: reverse-engineered networks ignore a wealth of existing mechanistic information about individual proteins and reaction intermediates, whereas literature-based networks are too disconnected from functional data to encode input–output relationships. Thus, even the most comprehensive interactomes do not capture the logic of cellular biochemistry and—critically—cannot predict the responses of cells to specific biological stimuli. Two nodes in a node–edge graph might have a positive effect on a downstream node, but a graph alone cannot specify whether the target is active when only one upstream node is active or whether both must be on.

Setting aside our own views on global warming, it is instructive to compare network emergence to peer review, as it is critiqued by Martin Kozlowski’s illustration inserted in the image above. In the future will selected scientists continue “write the book” by judging their peers? Or will every shade of opinion compete in the open network where the most respected ideas will rise to prominence? I think the latter.

Here is a pertinent bit from today’s Wall Street Journal opinion piece where I found the Kozlowski drawing:

But there’s something much, much worse going on—a silencing of climate scientists, akin to filtering what goes in the bible, that will have consequences for public policy, including the Environmental Protection Agency’s (EPA) recent categorization of carbon dioxide as a “pollutant.”

The bible I’m referring to, of course, is the refereed scientific literature. It’s our canon, and it’s all we have really had to go on in climate science (until the Internet has so rudely interrupted). When scientists make putative compendia of that literature, such as is done by the U.N. climate change panel every six years, the writers assume that the peer-reviewed literature is a true and unbiased sample of the state of climate science.
[emphasis mine]

The time is long overdue for scientists and experts in all academic fields to no longer turn their backs on the network laws that have made peer review obsolete.

In a speech given just a few weeks before he was lost at sea off the California coast in January 2007, Jim Gray, a database software pioneer and a Microsoft researcher, sketched out an argument that computing was fundamentally transforming the practice of science.

Dr. Gray called the shift a “fourth paradigm.” The first three paradigms were experimental, theoretical and, more recently, computational science. He explained this paradigm as an evolving era in which an “exaflood” of observational data was threatening to overwhelm scientists. The only way to cope with it, he argued, was a new generation of scientific computing tools to manage, visualize and analyze the data flood.

In essence, computational power created computational science, which produced the overwhelming flow of data, which now requires a computing change. It is a positive feedback loop in which the data stream becomes the data flood and sculptures a new computing landscape.

The image posted above is from a screenshot of how Google’s “Wonder wheel” search feature offers related subjects for a search for “Organelles of the Eukaryotic Cell.” The search returned about 518,000 data links for organelles.

The education establishment has dealt with the abundance of data Jim Gray described primarily by screening and choosing for students. The practice has been to deliver pre-selected knowledge items via standards, textbooks, curricula, and courses — all of which are creatures of the analog age now almost over. Education has yet to embrace the reality that computing is fundamentally transforming the practice of engaging knowledge.

Education as the selective gatekeeper to learning inevitably will be swept away by the deluge of data available in the hands and pockets of essentially all students within a handful of years. Education must, as science must, give learners access to: a positive feedback loop in which the data stream becomes the data flood and sculptures a new computing education landscape.

A major step toward a more positive feedback to education is making resources findable at the node level at the time experts put their subject knowledge online. The effect of that is to open the gates of knowledge, connecting those who know the most to those who would learn their subjects.

Any time an elite group controls information published for a subject, at least some transparency is lost in what is excluded by the elite. The hope of peer review is that only the lesser stuff is excluded (made opaque). In complete contrast, network emergence is broadly transparent. The search engine principle invented at Google sends to the top of its search results the nodes visited by the most users, with known experts given more weight. The results are a long tail, where even the least of the nodes still appear somewhere down the list.

Education has not yet let the transparency of emergence operate for its online materials much at all. Most digital learning stuff is still controlled by businesses that pay elites to structure it by grade, standard, curricula and that keep it behind pay-for-it walls. For the most part, open educational materials (OER) are repositioned structured bundles (curricula, courses, lesson plans) that do not allow nodes to emerge from within very much.

It occurred to me when I read the following articles today that this breathtakingly simple principle is at work in both: In an open network emergent patterns are transparent. When small pieces (nodes) of an open network determine what connects to what online, what emerges and its long tail of related information are all transparent. The elites then have to complete like everyone else to give weight to the nodes causing those nodes and the patterns they make to become what is most used used. In the new Facebook system, the individual can decide what nodes to open into this emergent transparency.

Roger Simon: “Climategate is about a lot more than climate. It’s about science and its relationship to politics and profit, the academy, the state and, perhaps most importantly, information control. The manner through which we learn (or thought we did) important knowledge about key aspects of our existence, the way things are hidden, has been exposed in this one instance like the Wizard of Oz.”

Facebook founder Mark Zuckerberg wrote this week in “An Open Letter” to members that Facebook’s regional networks are “no longer the best way to control your privacy . . . . The plan we’ve come up with is to remove regional networks completely and create a simpler model for privacy control where you can set content to be available to only your friends, friends of your friends, or everyone. We’re adding something that many of you have asked for — the ability to control who sees each individual piece of content you create or upload. In addition, we’ll also be fulfilling a request made by many of you to make the privacy settings page simpler by combining some settings. . . .”

Downes, Downes, Wiley

For the record, I think a lot of OER is something academics do to reposition their pedagogy from the analog education era. OER tends to be bundled in courses and curricula and further boxed up into PDFs. The content of OER is seldom really open — urls for interesting content are not online and if they are, not tagged for search engine spiders. The content in OER that most students and teachers would like to use is the many nodes of stuff to learn within the bundles. To fix this disconnect the bundles do not even have to be disturbed. Just put a second version of them online and SEO the nodes within. OER needs SEO (search engine optimization).

To my point, there is a recent PLoS (Public Library of Science)  article about why they are providing a new metric for assessing citations of articles instead of journals (that is nodes instead of bundles).

Grist to chew on in future OER discussions . . . .

Search engine spiders collect information about activity related to zillions of internet ants (keywords, etc.) and about what synapses (webpage links) are doing. Based on the concert of this activity search engines make decisions on ranking a webpage. I suggest that if you are interested in how emergent complexity creates findability on the internet, reading the SEED article will loosen up your synapses for pondering this fascinating topic. Here is a sample from SEED:

Choosing a new home, or house hunting, is the most complicated decision an ant colony makes. When an ant nest is overcrowded or damaged, scout ants begin searching for a new building site by making independent evaluations of different spots and reporting back to the colony. A decision is made when a “quorum” is reached, when a certain number of ants agree on a location.

This same process occurs among neurons in a monkey’s visual cortex when the animal performs a visual discrimination task. In the task, a monkey is flashed an image of dots moving in different directions and must decide which way the majority of them are going. When the image appears, neurons in the monkey’s visual cortex gather bits of information from the monkey’s eyes, much like ants evaluating a nest site. As more data is gathered, the neurons with the correct answer gradually increase their firing rate. When their activity reaches a certain threshold level, the monkey makes a decision.

Thus, decisions in both brains and ant colonies are based on thresholds that can be adjusted for either speed or accuracy. Understanding how these mechanisms work “will not only advance our understanding of collective decision making by social insects and individual decision making by vertebrates, but could potentially give us ways to design machines for tackling these kinds of problems,” [researcher James] Marshall says.

One of “these kinds of problems” is adjusting the thresholds of link placement on search engine results pages. Millions of people (think ants) at any moment in time are making decisions on which webpage to open and/or link to (think neuron). It is the collectivity of these decisions that determines online findability.