Mar
22
The Atomization of Education
Filed Under Big Data, Blog, Cengage, eBook, Education, eLearning, Industry Analysis, internet, news media, Pearson, Publishing, Uncategorized, Workflow | Leave a Comment
When lofty, intellectual figures like Mike Shatzkin (http://www.idealog.com/blog/atomization-publishing-as-a-function-rather-than-an-industry/) quote one’s sayings of many years ago there is real danger of a sudden rush of blood to the head. Thankfully, his purpose is more to mark the entry of Google as a publisher than to say “Worlock told you so”, but he really started me rethinking this turf in the process. You see, “atomization” is the growing experience of all markets. Nature, this week, described the work of a computational biologist at a drug company, searching 23,000 articles in one text mining enquiry” to pick out hundreds of proteins that could relieve a mouse model of multiple sclerosis”. This is not the world of articles and journals in which most journal publishers think they are still living. The practice of law is a workflow now designed around procedural requirements fed by precedents. Readers here will have heard almost ad nauseam of the collapse of newspaper and magazine business models, replaced online and in the device in your hand with filtered references and the ability to call for more. Artificial intelligence and computer written information ( Narrative Science) will take an ever larger role in content creation, and this content will be increasingly read by machines that protect us from the full onslaught of the information-based networked society that we have created. And that machine-generated information will be created in atoms from the very beginning. Addressable, metadata-identifiable atoms. We will collect them, review them, put them into different orders and create, from these objects, the information structures of the future – and some of them we shall probably call “books” just because we cannot think of a better name.
Amongst my reading this week has been a pair of reports from Eduventures (www.eduventures.com) on Predictive Analytics and Adaptive Learning. While they do not take us very far they do very adequately describe the present and I am delighted to see subjects like this being covered in contexts where educational administrators may get to read them. The educational mold probably broke about a decade ago, and much of what now happens in education reflects the dim and distant echoes of the works of true scholars like Seymour Pappert and Marvin Minsky at MIT, or Alan Kay at Zerox and Apple. But for all that long decade of talking about learning objects and SCORM, of learning journeys and personalized learning, where are we now? Still talking about “the migration to the electronic textbook”!
And why? Publishers say teachers demand texts, Teachers say students demand them. Everyone says parents insist on them, only please make them digital (easier to carry, cheaper to buy). And in every part of the developed world you hear the low moan of “falling standards, education is not gripping or immersive, kids are now exam monkies being trained to pass tests etc etc”. The inescapable conclusion is that our society is in denial in the education space so maybe our thinking should be turning towards what we do to change the fundamentals. And here the Eduventures work carries seeds of hope. The report which looks at adaptive learning focusses on “developmental education (for European readers, this is yet another euphemism for remedial work with less able learners). And this is critical in all of our societies: only where most traditional techniques failed completely will we seem to trust ourselves to something else. So where students must play catch-up we can go to people like Pearson Learning Solutions, who by investment or partnership have now put together a considerable hand of potential plays, from SmartThinking in the US to TutorVista in India covering the individualized instruction side of the deal, while the work with Knewton, mentioned here before, moves Pearson centrally into the service-led domain centred on creating course material for specific students with known and diagnosed problems, and making it adapt with them. Only the complete atomization of learning materials into objects with defined learning outcomes will allow these solutions to succeed, and publishers to survive. And yet, this outcome is still far from the minds of the biggest “textbook” publishers in the line behind Pearson.
Who else does good work in adaptive learning, then? Eduventures single out Carnegie Learning, now part of Apollo (the University of Phoenix, not the investor). Here is one of the future patterns: owners of schools and distribution systems, like Pearson and Apollo, custom to their own needs while the textbook players just melt in the heat. Another quoted player is Edmentum (PLATO plus Archipelago), now refinanced and with a strong bias to the developmental education field. Meanwhile a quite different and disruptive set of players are atomizing at the teacher level. Beyond the scope of these reports, note how rapidly systems are developing all over the world to network successful lessons, resources and techniques. When I was a textbook publisher our mantra, in times when the only tech was Monotype, was that we justified our existence by reflecting through our authors the best teaching practice that we could research and locate. Now every teacher can do that for themselves: TSL Education claims a network outreach to 47 million teachers globally from its UK and US sites, while teacherspayteachers.com publicizes a teacher in North Carolina who has earnt $1 million from selling learning resources online. Atomization pays!
But the revolution comes full turn when you apply predictive analytics. Education is a live Big Data environment, with huge caches of material concerning each learner, and increasingly, each learner’s reaction to each learning process. At the moment, these reports note, the focus of predictive analytics is finding out who is likely to fail and trying to help them in time. With 25% of US college learners dropping out before the end, this is a very expensive problem which needs to be solved. Predictive Analytics can be demonstrated to improve retention, both by improving selection and by diagnosing reasons for failure before it is too late. College teaching staff will be worried: failure to learn is also about failure to teach. Typically, the interviews in these reports show that data is siloed, that LMS data does not mix well with other content, that those who use predictive analysis mostly do so in terms of IBM’s SPSS software, and that the use of these analytic techniques was just as prevalent now in retention as in recruitment. Just what one would have expected. But when data analytics becomes an accurate prediction of outcomes, then personalized learning can really begin. Do not be stubbornly publishing textbooks, whether they are digital facsimiles or not, when that golden dawn arrives!