Every day we happily agree to sharing enormous amounts of information about ourselves to a wide range of companies. All those club cards we carry around which register every purchase we make and gather various kinds of bonus points that some day can be cashed in for discount. The reward to the company is tons of data about our preferences, purchasing habits and spending power that can then be used for targeted advertising and as statistical data for marketing analysis. Free has a price tag.
The same goes for all the free web services we know and love, bringing you, among millions of other things, this blog. The price of free is offering a vast amount of raw data that companies can then analyse to then offer services back to us or as strategic marketing data. As the saying goes "if it's free, you're probably the product." Google, Facebook, Apple, Microsoft and all the others are collecting all our clicks for future harvesting and it's not hard to see that maybe that is one of the main drivers behind the MOOC trend. There's a lot of speculation about MOOC business models and although there are a few already in place they are probably not the reason the major MOOC players have attracted impressive amounts of venture capital.
An excellent presentation by Audrey Watters, Student Data is the New Oil: MOOCs, Metaphor, and Money (Hack Education 17 October), raises possible the real motivation behind MOOCs, namely the promise of data mining. Data it seems is the new oil and we are only just beginning to be able to refine it and put it to use. By storing all your clicks, which sites you visit, browsing patterns, videos watched, tweets sent, test scores and so on you can build up incredibly detailed profiles of every user. This can be used to be able to suggest new content specially for you, predict how you will behave, assess your learning and so on. Learning analytics has been on the radar of the Horizon Report for a few years now but the technology to fully realise the potential is only beginning to emerge.
Student data could well be digital oil and companies that can store the most will soon be able to refine it into useful commodities and Watters suggests that the scramble to own the oil reserves has only just begun. Until now this data was stored in many separate silos but these are being linked together and the next stage of web development will see completely new ways of utilizing and monetizing the raw data. Learning analytics promise personalized education where the net will guide you through customized learning paths suggesting material and methods suited to what works best for you. There are almost unlimited opportunities here but there's also a more sinister side if all this data gets into the wrong hands. Watters quotes from journalist Jer Thorp:
"Perhaps the “data as oil” idea can foster some much-needed criticality. Our experience with oil has been fraught; fortunes made have been balanced with dwindling resources, bloody mercenary conflicts, and a terrifying climate crisis. If we are indeed making the first steps into economic terrain that will be as transformative (and possibly as risky) as that of the petroleum industry, foresight will be key. We have already seen “data spills” happen (when large amounts of personal data are inadvertently leaked). Will it be much longer until we see dangerous data drilling practices? Or until we start to see long term effects from “data pollution”?
The analogy with oil is an excellent warning of the potential and dangers of digging too deep. Here's Audrey Watters' slideshow that accompanies the talk.
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